Suno Ai Api Docs Jobs in Usa

Join the team leading the next evolution of virtual care.

At Teladoc Health, you are empowered to bring your true self to work while helping millions of people live their healthiest lives.

Here you will be part of a high-performance culture where colleagues embrace challenges, drive transformative solutions, and create opportunities for growth. Together, we're transforming how better health happens.

Summary of Position

As a Staff Software Engineer, you are a senior individual contributor who leads the design and delivery of significant platform features and raises the bar for engineering quality across the team. You'll work handson in code-designing APIs and data flows, building services in Python/FastAPI and React frontends, and guiding solutions from idea to production. You'll mentor engineers, influence architecture and standards within and adjacent to your team, and partner closely with product and design to achieve clear, measurable outcomes. This role blends deep implementation work with pragmatic technical leadership by example.

Essential Duties and Responsibilities

• Lead technical design for platform features and services, breaking ambiguous requirements into clear, incremental designs and stories for your team and adjacent partners.

• Implement backend services in Python/FastAPI and React frontends end-to-end, owning a continuous stream of stories from idea to production.

• Define and use clear API contracts and data flows between services and UIs, creating patterns and templates others can follow.

• Champion high-quality engineering practices, including code reviews, documentation, and maintainable, testable designs.

• Develop and improve automated testing (unit, integration, endtoend) and integrate these into everyday development and CI.

• Improve CI/CD pipelines and release workflows for your team so the team can ship small, safe changes frequently and confidently.

• Own the operational lifecycle of the features and services you build, including monitoring, observability, on-call participation, and incident follow-up.

• Design and implement secure-by-default solutions, including robust authentication/authorization, input validation, and safe handling of sensitive data.

• Identify and address reliability and performance risks early, proposing concrete technical improvements and sequencing them into the roadmap.

• Mentor and unblock engineers through pairing, design discussions, and clear feedback; influence without formal authority.

• Partners with product/design to shape requirements into incremental deliverables; escalates tradeoff decisions; proposes sequencing that optimizes value/risk.

The time spent on each responsibility reflects an estimate and is subject to change dependent on business needs.

Supervisory Responsibilities

No

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field; equivalent work experience is acceptable.

• 7+ years of experience in software engineering.

• Strong proficiency with Python and modern web backends (FastAPI, Flask, Django, or similar) and solid understanding of HTTP, API design, and data modeling.

• Significant experience with React (or a comparable SPA framework) and building production frontends that talk to backend APIs.

• Demonstrated ability to own features end-to-end in a small team: from shaping requirements through design, implementation, testing, deployment, and support.

• Experience designing and working with distributed systems or multi-service architectures (e.g., service boundaries, async jobs, integration patterns).

• Solid understanding of observability and operations for production systems (metrics, logs, traces, dashboards, alerting, incident response).

• Strong understanding of security fundamentals (authentication, authorization, secure data handling) and how they apply to web services and UIs.

• Deep familiarity with automated testing and CI/CD, and a track record of improving engineering workflows and quality.

• Excellent communication and collaboration skills; comfortable working closely with product, design, and other stakeholders.

• Proven ability to provide technical leadership in a hands-on way: unblocking others, making clear decisions, and raising the bar through code and reviews.

Bonus Qualifications

• Experience in early-stage or small platform teams where engineers wear multiple hats and balance shipping with building foundations.

• Experience with Azure and containerized deployments (or similar cloud-native environments).

• Experience building platforms (developer platforms, data platforms, or similar) that serve multiple product teams.

• Exposure to AI/ML or data-intensive applications (e.g., integrating with model inference APIs, data pipelines, or analytical data stores).

The base salary range for this position is$180,000 - $200,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2026.Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications.This information is applicable for all full-time positions.

#LI-SS2 #LI-Remote

We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. All time off must be approved by your manager prior to use. You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. This applies to full-time positions only. If you are applying for a part-time role, your recruiter can provide additional details.

As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. Applicants who falsify information will be disqualified.

Teladoc Health will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

Why join Teladoc Health?

• Teladoc Health is transforming how better health happens. Learn how when you join us in pursuit of our impactful mission.

• Chart your career path with meaningful opportunities that empower you to grow, lead, and make a difference.

• Join a multi-faceted community that celebrates each colleague's unique perspective and is focused on continually improving, each and every day.

• Contribute to an innovative culture where fresh ideas are valued as we increase access to care in new ways.

• Enjoy an inclusive benefits program centered around you and your family, with tailored programs that address your unique needs.

• Explore candidate resources with tips and tricks from Teladoc Health recruiters and learn more about our company culture by exploring #TeamTeladocHealth on LinkedIn.

As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status, or pregnancy). In our innovative and inclusive workplace, we prohibit discrimination and harassment of any kind.

Teladoc Health respects your privacy and is committed to maintaining the confidentiality and security of your personal information. In furtherance of your employment relationship with Teladoc Health, we collect personal information responsibly and in accordance with applicable data privacy laws, including but not limited to, the California Consumer Privacy Act (CCPA). Personal information is defined as: Any information or set of information relating to you, including (a) all information that identifies you or could reasonably be used to identify you, and (b) all information that any applicable law treats as personal information. Teladoc Health's Notice of Privacy Practices for U.S. Employees' Personal information is available at this link.

Join the team leading the next evolution of virtual care.

At Teladoc Health, you are empowered to bring your true self to work while helping millions of people live their healthiest lives.

Here you will be part of a high-performance culture where colleagues embrace challenges, drive transformative solutions, and create opportunities for growth. Together, we're transforming how better health happens.

Summary of Position

The Principal AI Security Engineer is a senior technical leader on the AI Security team, responsible for designing, building, and operating security controls for generative AI and Machine Learning (ML) systems across their full lifecycle: data, training, deployment, and runtime.

This role is deeply hands-on: you will work directly with data science, MLOps, platform, devops and application teams to secure LLMs, RAG systems, AI agents, and AI-enabled products. You will also lead the intake and review process for AI use cases, helping the organization adopt AI safely and at scale in a highly regulated environment.

The ideal candidate combines:

* Strong security engineering and cloud architecture experience

* Deep, current familiarity with modern AI/LLM tooling and practices

* Familiar and can cover basic coding within the AI tooling space (python, others)

* The ability to communicate clearly with senior leadership and influence enterprise-wide strategy

Essential Duties and Responsibilities

Secure AI / ML platforms and workloads

* Lead security architecture and threat modeling for AI/ML systems, including LLMs, RAG pipelines, agents, and AI-powered applications.

* Design and implement security controls as code (services, libraries, infrastructure-as-code, policy-as-code) for AI/ML platforms and workloads.

* Lead and help setup the basic infrastructure needed to safely rollout AI - MCPs, LLMs, pipelines, Test harness for AI (ie: harmbench), intake automation.

* Partner with data science and MLOps teams to harden:

• Data ingestion and labeling
• Training and fine-tuning pipelines
• Model registries and deployment workflows
• Inference APIs, agents, and integrations

* Define and champion secure reference architectures and patterns for common AI use cases and focus on composable architecture.

AI use case intake & governance

* Design, implement, and continuously improve the intake, triage, and review process for AI/ML and generative AI use cases across the organization.

* Build and automate self-service workflows (e.g., request forms, risk questionnaires, routing, approvals) that balance speed of delivery with security, privacy, and compliance with a focus on risk scoring and scorecards.

* Define risk-based criteria for AI use case approval, including data sensitivity, model and vendor selection, integration patterns, and control requirements; this will involve in re-mapping the complete end to end lifecycle.

* Review proposed AI solutions from concept through deployment, providing clear, actionable guidance to product and engineering teams.

* Maintain visibility into the AI use case portfolio and risk posture, and provide regular reporting to leadership and governance bodies.

Monitoring, detection & assurance

* Establish and maintain monitoring and detection for AI-specific threats, such as:

• Prompt injection and jailbreak attempts
• Data exfiltration and sensitive data exposure
• Misuse or abuse of AI tools and agents
• Anomalous model or pipeline behavior

* Integrate AI/ML systems with existing logging, SIEM, and incident response processes.

* Lead or participate in AI-focused security assessments, red-teaming, and adversarial testing; drive remediation and verification.

Strategy, leadership & enablement

* Help define and evolve the organization's AI security strategy, standards, and roadmap in partnership with Security, Engineering, Data, Legal, Privacy, and Risk.

* Translate global privacy, data sovereignty, and regulatory requirements into practical technical controls for AI workloads across multiple cloud environments.

* Prepare and deliver executive-ready briefings and narratives on AI security risks, controls, and progress.

* Mentor other engineers and serve as THE internal subject matter expert on AI/ML security, generative AI, and LLM-based systems.

Qualifications Expected for Position

• 7+ years of experience in information security, security engineering, or related fields, including significant time building and securing production systems.
• 3+ years of hands-on experience with AI/ML technologies (such as LLMs, RAG, model training/fine-tuning, MLOps, or AI-powered products), including implementation of security controls or guardrails for these systems.
• Strong programming skills in one or more relevant languages (e.g., Python, TypeScript/JavaScript, Go, or similar), with a track record of contributing to production-grade tools, services, or libraries.
• Deep understanding of cloud security architecture and controls on at least one major cloud platform (AWS, Azure, or GCP), including identity, networking, secrets management, data protection, logging, and monitoring.
• Experience designing and implementing controls in a highly regulated environment; healthcare or financial services preferred.
• Demonstrated ability to lead complex technical initiatives across multiple teams, from problem definition through design, implementation, and adoption.
• Proven ability to communicate complex technical and risk topics clearly to both engineering teams and senior leadership.

Preferred Qualifications:

* Practical experience securing LLM- and genAI-based systems, such as:

• RAG architectures backed by internal data
• AI assistants, copilots, or agents integrated with enterprise tools
• Fine-tuned models and model hosting platforms

* Experience with AI IDE tools

• cursor, windsurfer, others
• Knows the security problems and has practical solutions that balances innovation with innovation.

* Familiarity with AI/ML frameworks and ecosystems (e.g., TensorFlow, PyTorch, Scikit-learn) and/or modern LLM development stacks and IDEs (e.g., API-based LLMs, self-hosted models, AI-enhanced coding tools).

* Experience with:

• Security for data pipelines, feature stores, and model registries
• Detection engineering or SIEM tuning for AI-related events
• Red-teaming or adversarial testing of AI systems

* Evidence of ongoing engagement with AI and security (such as side projects, open-source contributions, lab environments, publications, or conference talks).

* Familiarity with emerging AI security and safety standards and forward-looking industry guidance and horizon reports.

* Relevant certifications (e.g., cloud security, security engineering, or governance) are a plus.

* Strong analytical and problem-solving skills, with the ability to operate effectively in a fast-evolving technical and regulatory landscape.

* High level of integrity and ethical conduct.

This role is a fit if you:

* Regularly build, break, or secure AI/ML or LLM-based systems in your day-to-day work or personal projects.

* Are comfortable reading and writing code, experimenting with new AI tools, and wiring them into real systems.

* Enjoy turning ambiguous AI ideas and risks into concrete architectures, controls, and automation.

* Can move fluidly between deep technical discussions and concise, executive-level explanations.

This role is not a fit if you:

* Prefer to focus solely on policy, governance, or vendor assessments without hands-on technical work.

* Do not actively engage with current AI/LLM tooling, research, and emerging practices.

* "Describe a specific LLM or AI/ML system you have secured. What were the main risks and what controls did you implement?"

* "What AI tools, libraries, or environments do you actively use or experiment with today (work or personal), and for what?"

* "What do you see as the most important AI security or safety developments on the horizon over the next few years, and why?"

The base salary range for this position is$180,000 - $190,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2026.Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications.This information is applicable for all full-time positions.

We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. All time off must be approved by your manager prior to use. You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. This applies to full-time positions only. If you are applying for a part-time role, your recruiter can provide additional details.

As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. Applicants who falsify information will be disqualified.

Teladoc Health will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

Why join Teladoc Health?

• Teladoc Health is transforming how better health happens. Learn how when you join us in pursuit of our impactful mission.

• Chart your career path with meaningful opportunities that empower you to grow, lead, and make a difference.

• Join a multi-faceted community that celebrates each colleague's unique perspective and is focused on continually improving, each and every day.

• Contribute to an innovative culture where fresh ideas are valued as we increase access to care in new ways.

• Enjoy an inclusive benefits program centered around you and your family, with tailored programs that address your unique needs.

• Explore candidate resources with tips and tricks from Teladoc Health recruiters and learn more about our company culture by exploring #TeamTeladocHealth on LinkedIn.

As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status, or pregnancy). In our innovative and inclusive workplace, we prohibit discrimination and harassment of any kind.

Teladoc Health respects your privacy and is committed to maintaining the confidentiality and security of your personal information. In furtherance of your employment relationship with Teladoc Health, we collect personal information responsibly and in accordance with applicable data privacy laws, including but not limited to, the California Consumer Privacy Act (CCPA). Personal information is defined as: Any information or set of information relating to you, including (a) all information that identifies you or could reasonably be used to identify you, and (b) all information that any applicable law treats as personal information. Teladoc Health's Notice of Privacy Practices for U.S. Employees' Personal information is available at this link.

Join the team leading the next evolution of virtual care.

At Teladoc Health, you are empowered to bring your true self to work while helping millions of people live their healthiest lives.

Here you will be part of a high-performance culture where colleagues embrace challenges, drive transformative solutions, and create opportunities for growth. Together, we're transforming how better health happens.

Summary of Position

Essential Duties and Responsibilities

• Work closely with business stakeholders toidentifyautomation opportunities.
• Lead the technical set up and integration ofconversational AI platform & agent development studiowithin the enterprise environment.- copilot agents preferred, deploying across enterprise not for personal use.
• Analyze business processes, data flows, and system architectures to support AI solution design.
• Support configuration and deployment of AI-powered agents,applications,and workflows.
• Design,build,and customize AI agents to automate workflows and improve productivity.
• Utilizedata platforms such asMicrosoft Fabric, Snowflake, Databricks, AWSfor data orchestration, governance, and compliance.
• Ensure seamless interoperabilityof agentsacrossMicrosoft and other enterprise applications asrequired.
• Evaluateand implement secure API integrationswith enterprise systems using APIsandconnectors to enable data exchange and workflow automation.
• Apply best practices for data security, identity management, and compliance with organizational and regulatory standards.
• Apply analytical judgment to assess feasibility, scalability, data readiness, and risks of AI use cases.
• Collaborate withcybersecurityand product teams to build robust AI solutions
• Test new AI agent enhancements, integrations, and fixes prior to release to ensure quality and expected behavior.
• Track and analyze performance metrics, including response quality, speed, reliability, andcost-effectivenessof AI agents and automated workflows.
• ContinuouslyoptimizeAI solutions based on performance data, user feedback, and evolving business needs.
• Document requirements, solution designs, architecture diagrams, and integration approaches in a clear and concise manner.
• Contribute to internal standards, reusable patterns, and best practices for AI agent and automation development.
• Support knowledge sharing and enablement across technical and business teams.

Qualifications Expected for Position

• Bachelor's degree in computer science, Information Systems, Engineering, Data Science, or a related fieldor equivalent combination of education and relevant professional experience.
• Advanced certifications or coursework in cloud platforms, data engineering, or AI/ML preferred.
• 3+years of experience in solution architecture, systems integration, automation engineering, or applied AI roles.
• 1+ year demonstrated ability to design, build, and deployAI-poweredagents, workflows, or conversational applications.
• Proven experience working directly with business stakeholders to translate operational needs into scalable technical solutions.
• Hands-on experience implementing enterprise automation or conversational AI solutions across multiple departments or use cases.
• Experienceoperatingin regulated orsecurity-consciousenvironments, supporting compliance and governance requirements.
• Strong experience designing and implementing enterprise system integrations using APIs, connectors, and automation frameworks.
• Experience working with modern data platforms (e.g.,Microsoft Fabric, Snowflake, Databricks, AWS) to support data orchestration, access control, and compliance.
• Solid understanding of identity management, access controls, and data security best practices.
• Ability to assess AI solution feasibility, including data readiness, scalability, performance, and cost considerations.
• Strong analytical andproblem-solvingskills with the ability to apply sound judgment to ambiguous or emerging AI use cases.
• Excellent written and verbal communication skills, with the ability to explain technical concepts to nontechnical audiences.

The base salary range for this position is$130,000 - $140,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2026.Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications.This information is applicable for all full-time positions.

We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. All time off must be approved by your manager prior to use. You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. This applies to full-time positions only. If you are applying for a part-time role, your recruiter can provide additional details.

As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. Applicants who falsify information will be disqualified.

Teladoc Health will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

Why join Teladoc Health?

• Teladoc Health is transforming how better health happens. Learn how when you join us in pursuit of our impactful mission.

• Chart your career path with meaningful opportunities that empower you to grow, lead, and make a difference.

• Join a multi-faceted community that celebrates each colleague's unique perspective and is focused on continually improving, each and every day.

• Contribute to an innovative culture where fresh ideas are valued as we increase access to care in new ways.

• Enjoy an inclusive benefits program centered around you and your family, with tailored programs that address your unique needs.

• Explore candidate resources with tips and tricks from Teladoc Health recruiters and learn more about our company culture by exploring #TeamTeladocHealth on LinkedIn.

As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status, or pregnancy). In our innovative and inclusive workplace, we prohibit discrimination and harassment of any kind.

Teladoc Health respects your privacy and is committed to maintaining the confidentiality and security of your personal information. In furtherance of your employment relationship with Teladoc Health, we collect personal information responsibly and in accordance with applicable data privacy laws, including but not limited to, the California Consumer Privacy Act (CCPA). Personal information is defined as: Any information or set of information relating to you, including (a) all information that identifies you or could reasonably be used to identify you, and (b) all information that any applicable law treats as personal information. Teladoc Health's Notice of Privacy Practices for U.S. Employees' Personal information is available at this link.

AI Ethics Specialist, Standards, Measurement & Governance | Just Horizons Alliance

Join us to define the standards that hold AI systems accountable.

The situation

Just Horizons Alliance is an 18-year-old applied research lab focused on ethics and technology. Our current focus is the AI Ethics Index, a measurement framework for evaluating AI systems on ethics, safety, and societal impact.

We currently have a first version of the framework that is validated and in use. Now we're investing in the next phase: sharper indicator definitions, stronger construct validity, governance processes that hold up to external scrutiny, and measurements that work across domains from education to healthcare to finance.

This is the first dedicated hire to drive the standards and governance layer end-to-end.

What you'll actually do

Months 1–3: Learn the system

Work through the existing L4 indicator library with Sophia. Understand where definitions need tightening, which constructs require the most interpretation, and how the evaluation engine turns indicators into measurements. Start giving developers working definitions they can implement.

Months 4–6: Build the governance infrastructure

Lead the development of a versioning and change control process for the Index. Define disclosure policies. Formalize internal ethical oversight processes. Collaborate with domain experts in education, healthcare, and finance to validate indicators across contexts.

Months 7–12: Drive the standard

Be the person who gives definitive answers on construct interpretation. Manage the L4 indicator framework as a living, governed document. Represent the methodological rigor of the Index in external conversations with regulators, academics, and the organizations being evaluated.

Why this role is hard

You're working at the frontier of a field that does not have settled answers. There is no ISO standard for AI ethics measurement. The frameworks you're building will be contested by academics, challenged by the AI companies being evaluated, and scrutinized by regulators. You need to make defensible decisions under genuine uncertainty, document your reasoning clearly, and communicate it to people who will disagree.

The daily work involves uncomfortable specifics. What does \"sexually explicit content\" mean when an LLM is used in a youth education context—a tutoring app, a storytelling tool, an educational assistant? Where exactly is the boundary? You have to define it in terms a developer can implement and an auditor can verify.

The pace is weeks, not semesters.

You're probably the right person if

You've taken an abstract ethical principle and turned it into something a developer could build or a compliance team could audit

You understand NIST AI RMF or the EU AI Act at a working level — not awareness, but enough to argue about the details

You have external credibility in the field: publications, recognised work, advisory roles, or a title that carries weight

KYC, compliance, or governance experience is part of your background alongside ethics expertise

You work at the pace of decisions, not the pace of studies

You can hold a substantive conversation with a software developer about API behaviour and with a philosopher about construct validity — on the same day

You can read an inter-rater reliability methodology and understand what it means for your indicator definitions

You're probably not the right fit if

Your background is purely academic ethics — you've written and published but never operationalized anything

You need months of research before committing to a position on a specific indicator definition

You're primarily a communicator or writer about AI ethics rather than a practitioner of governance

You're based on the West Coast US or don't work in East Coast US or Western Europe time zones

You see \"working with developers\" as someone else's job

Hard Skills

These are the domain and technical capabilities you need going in — or need to be able to build up fast. You don't need to be an engineer. But you do need to learn quickly, including using AI tools to close knowledge gaps on the fly.

• NIST AI RMF and EU AI Act — working-level knowledge, not awareness. Enough to argue about the details and identify where a specific AI system fails to comply
• Construct operationalization — demonstrated experience translating an abstract ethical principle into a bounded, testable indicator that someone else can use
• Governance documentation — writing versioning policies, change control frameworks, and disclosure protocols that other people actually use day to day
• AI evaluation methodology — familiarity with how AI systems are benchmarked, where measurement goes wrong, and what validity means in a scientific context
• Basic technical literacy — able to read API documentation, understand what a model endpoint does.
• Statistical reliability concepts — inter-rater reliability, aggregation methods, and what it means for a measurement to be valid versus merely reliable
• KYC or compliance frameworks — experience building governance processes that have real enforcement teeth, not just principles documents that no one is held to

What you get

The role: Work directly with Sophia Zitman (AIEI Team Lead) as the person who owns the methodological integrity of the AI Ethics Index. Direct daily collaboration with the development team.

The comp: $110,000

The team: Small, split between ethicists and engineers. Interview panel: Janet Kang and Sophia Zitman.

The environment: Boston-based non-profit (501(c)(3)). East Coast US or Western Europe time zones strongly preferred. Deliberate, rigorous culture.

The upside: You'll have built the governance foundation of what may become the globally referenced standard for AI ethics measurement. That is a genuinely consequential body of work.

Job Title: Sr AI Platform Engineer- AI Platform Engineer (Guardrails, Observability & Evaluation Infrastructure)

Location, Charlotte, NC, USA (3 days onsite)

Role Overview

AI Platform Engineer to design and build the foundational components that power enterprise scale GenAI applications. This includes data guardrails, model safety tooling, observability pipelines, evaluation harnesses, and standardized logging/monitoring frameworks. This role is critical for enabling safe, reliable, and compliant AI development across multiple use cases, teams, and business units. Idea is to create the common platform services that AI team will build upon.

Key Responsibilities

1. Guardrails, Safety & Governance

• Design and implement data guardrail frameworks (pre processing, redaction, PII/PHI filtering, DLP integration, prompt defenses).

• Build "Model Armor" components such as:

o Input validation & sanitization

o Prompt injection defenses

o Harmful content detection & policy enforcement

o Output filtering, fact checking, grounding checks

• Integrate safety tooling (policy engines, classifiers, DLP APIs, safety models).

• Collaborate with Security, Compliance, and Data Privacy teams to ensure frameworks meet enterprise governance requirements.

2. Observability Frameworks

• Build and maintain observability pipelines using tools like Arize AI (tracing, quality metrics, dataset drift/hallucination tracking, embedding monitoring).

• Define and enforce platform wide standards for:

o Tracing LLM calls

o Token usage and cost monitoring

o Latency and reliability metrics

o Prompt/model version tracking

• Provide reusable SDKs or middleware for engineering teams to adopt observability with minimal friction.

3. Logging, Monitoring & Telemetry

• Design standardized LLM-specific logging schemas, including:

o Inputs/outputs

o Model metadata

o Retrieval metadata

o Safety flags

o User context and attribution

• Build monitoring dashboards for performance, cost, anomalies, errors, and safety events.

• Implement alerting and SLOs/SLIs for LLM inference systems.

4. Evaluation Infrastructure

• Architect and maintain evaluation harnesses for GenAI systems, including:

o RAG evaluation (faithfulness, relevance, hallucination risk)

o Summarization/QA evaluation

o Human-in-the-loop review workflows

o Automated eval pipelines integrated into CI/CD

• Support frameworks such as RAGAS, G Eval, rubric scoring, pairwise comparisons, and test case generation.

• Build reusable tooling for teams to write, run, and track model evaluations.

5. Platform Engineering & Reusable Components

• Develop shared libraries, APIs, and services for:

o Prompt management/versioning

o Embedding pipelines and model wrappers

o Retrieval adapters

o Common data loaders and document preprocessing

o Tool/function schemas

• Drive consistency across teams with standards, reference architectures, and best practices.

• Review system designs across use cases to ensure alignment to platform patterns.

6. Collaboration & Enablement

• Partner with AI engineers, product teams, and data scientists to understand cross cutting needs and convert them into reusable platform features.

• Create documentation, onboarding guides, examples, and developer tooling.

• Provide internal training (brown bags, workshops) on guardrails, observability, and evaluation frameworks.

Required Qualifications

Technical Skills

• 5–10+ years software engineering or ML infrastructure experience.

• Strong Python engineering fundamentals (FastAPI, async, typing/Pydantic, testing).

• Experience with model safety/guardrails approaches (prompt injection defense, PII redaction, toxicity filters, policy enforcement).

• Hands on with Arize AI, LangSmith, or similar LLM observability platforms.

• Experience creating evaluation frameworks using RAGAS, G Eval, or custom rubric systems.

• Strong familiarity with vector databases (Pinecone, Weaviate, Milvus), embeddings, and retrieval pipelines.

• Solid understanding of LLM architectures, tokenization, embeddings, context limits, and RAG patterns.

• Experience in cloud (GCP preferred), Kubernetes/GKE, containers, and CI/CD.

• Strong understanding of security, governance, DLP, data privacy, RBAC, and enterprise compliance requirements.

Soft Skills

• Strong documentation and communication skills.

• Ability to influence engineering teams and standardize best practices.

• Comfortable working across multiple stakeholders—platform, security, ML engineering, product.

Nice to Have

• Experience with LangChain/LangGraph or LlamaIndex orchestrations.

• Experience with , Rebuff, Protect AI, or similar LLM security tooling.

• Experience with GCP Vertex AI pipelines, Model Monitoring, and Vector Search.

• Familiarity with knowledge graphs, grounding models, fact checking models.

• Building SDKs or developer frameworks adopted across multiple teams.

• On prem or hybrid AI deployment experience.

MatchPoint Solutions is a fast-growing, young, energetic global IT-Engineering services company with clients across the US. We provide technology solutions to various clients like Uber, Robinhood, Netflix, Airbnb, Google, Sephora, and more! More recently, we have expanded to working internationally in Canada, China, Ireland, UK, Brazil, and India. Through our culture of innovation, we inspire, build, and deliver business results, from idea to outcome. We keep our clients on the cutting edge of the latest technologies and provide solutions by using industry-specific best practices and expertise.

We are excited to be continuously expanding our team. If you are interested in this position, please send over your updated resume. We look forward to hearing from you!

Job Title: Embedded AI Engineer

Location: Sunnyvale, CA

Employment Type: 6+ Month Extendable Contract

Pay Range: USD 70-80/HR

- Role Overview/Job Responsibilities

About this opportunity – Embedded AI Engineer We are seeking an experienced Embedded AI Engineer to join our team in validating PyTorch-based Large Language Models (LLMs) using CUDA SDK APIs. The successful candidate will be responsible for debugging, extending, and replacing the underlying CUDA code to ensure seamless functionality on our company-specific AI processors.

Key Responsibilities:

● Validate PyTorch-based LLMs on company-specific AI processors using CUDA SDK APIs

● Debug and troubleshoot issues related to CUDA code integration with PyTorch models

● Extend and modify CUDA code to optimize performance on company-specific AI processors

● Replace existing CUDA code with custom implementations to meet specific requirements

● Collaborate with cross-functional teams to ensure successful integration of LLMs with company-specific AI processors

● Develop and maintain validation frameworks and tools for PyTorch-based LLMs

● Analyze and optimize the performance of LLMs on company-specific AI processors Requirements

● Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related fields

● Strong experience with CUDA programming and PyTorch framework

● In-depth knowledge of deep learning models, particularly Large Language Models (LLMs)

● Proficiency in C++ and Python programming languages

● Experience with debugging and troubleshooting complex software issues

● Excellent problem-solving skills and attention to detail

● Strong communication and collaboration skills

Nice to Have:

● Experience with AI processor architecture and design

● Knowledge of other deep learning frameworks, such as TensorFlow

MatchPoint Solutions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Local candidates only. You must be a W2 employee and we can not work with third party clients.

Software Engineer – Generative AI Applications |

Company’s Early Clinical Development (ECD) team is looking for a Software Engineer to design and build next‑generation applications that integrate generative AI into clinical development workflows. You’ll work with AI scientists, full‑stack engineers, and cross‑functional partners to deliver innovative, user‑centric tools that support Clinical Science, Operations, Medical Writing, Regulatory, and Quality teams.

What You’ll Do

• Develop and deploy software that integrates LLMs and AI‑driven capabilities
• Build intuitive front‑end interfaces and scalable backend services
• Design and maintain RESTful APIs and deployment pipelines
• Write clean, well‑documented, testable code; participate in code reviews
• Stay current on AI/ML advancements and evaluate new technologies
• Collaborate with data scientists, engineers, and product teams to embed AI into clinical development tools
• Monitor production systems and optimize performance

Who You Are

• Full‑stack engineer with strong experience building AI‑enabled applications
• Deep understanding of modern AI/LLM capabilities, limitations, and best practices
• Strong communicator who can work across scientific and technical teams

Minimum Requirements

• Bachelor’s or Master’s in CS, Engineering, Math, or related field
• 5+ years full‑stack development experience
• Expertise with Vue.js or React, plus backend frameworks (FastAPI, Django, Flask, Next.js)
• 2+ years building or deploying AI/ML applications
• Experience with REST APIs, prompt engineering, and containerized workflows (Docker, Kubernetes)
• Strong automated testing skills (unittest, jest, Playwright)
• Familiarity with Agile development
• Experience with AWS, Snowflake, and scalable system design
• Experience integrating LLMs, RAG systems, or chatbots

Preferred

• Experience with LLM fine‑tuning, AI agents, HuggingFace, LangChain, TensorFlow, or PyTorch
• Experience with Office.js add‑ins, WebSockets, JWT, or CRDTs (Yjs)
• Background using NLP/LLMs on clinical text or knowledge of clinical development

Position Title: Applied AI Systems Engineer

Location: Orange County, California (Hybrid)

Reports To: Head of Operations

Position Summary

This role is responsible for architecting, building, and deploying a production-grade AI operating system that automates core workflows across leasing, property management, accounting, construction coordination, and asset management.

The engineer will design and implement AI agents, document intelligence systems, and workflow automation pipelines that reduce manual processing, improve accuracy, and increase operational scalability across a commercial real estate portfolio.

This position requires strong systems thinking, rigorous technical execution, and the ability to translate complex operational processes into reliable automation.

Core Objectives

• Build an internal AI platform that automates high-volume operational workflows
• Reduce manual processing time and administrative overhead
• Improve accuracy, speed, and decision visibility across departments
• Establish scalable systems that support portfolio growth without proportional staffing increases

Primary Responsibilities

• AI Platform Architecture & Development
• Design and deploy AI agents to automate operational and administrative workflows
• Build LLM-powered systems for document review, data extraction, and decision support
• Develop retrieval-based systems leveraging leases, financial data, contracts, and SOPs
• Implement evaluation, monitoring, and continuous improvement frameworks

Lease & Document Intelligence Automation

• Build tools to extract key lease terms, obligations, and risk clauses
• Automates lease abstraction and document comparison workflows
• Develop compliance and deadline tracking systems
• Enable searchable knowledge retrieval across lease and legal documents

Leasing & Asset Management Automation

• Automate LOI comparison and deal workflow summaries
• Build dashboards summarizing tenant performance, lease milestones, and risk exposure
• Support market intelligence and tenant prospecting research
• Develop underwriting support and reporting tools

Property Management & Financial Workflow Automation

• Automate CAM reconciliation data processing and variance detection
• Streamline tenant reporting and communication workflows
• Track vendor contracts, compliance deadlines, and service obligations
• Extract and structure financial data from operational documents

Data Infrastructure & Knowledge Systems

• Structure internal documents and data for AI retrieval and automation
• Build document ingestion, indexing, and retrieval pipelines
• Implement vector search and knowledge retrieval systems
• Maintain data integrity, access control, and auditability

Systems Integration & Deployment

• Integrate AI tools with property management, accounting, CRM, and document platforms
• Deploy systems within secure cloud environments
• Implement logging, monitoring, performance, and cost controls
• Ensure reliability and scalability of deployed systems

Collaboration & Implementation

• Translate operational workflows into technical automation solutions
• Work directly with leadership to prioritize automation opportunities
• Train teams and implement adoption workflows
• Establish standards for responsible and secure AI usage

Required Qualifications

• Bachelor’s or advanced degree in Computer Science, Engineering, Mathematics, Statistics, or related quantitative discipline
• Demonstrated success in a rigorous academic or research environment
• 3–7+ years building production software, automation systems, or applied AI solutions
• Strong Python development and API integration experience
• Experience working with structured and unstructured data
• Experience deploying systems in cloud environments
• Strong understanding of system architecture and data pipelines
• Exceptional analytical and problem-solving ability

Preferred Qualifications

• Experience building document intelligence or contract analysis systems
• Experience with retrieval systems and vector databases
• Experience automating financial or operational workflows
• Experience integrating AI into business operations environments
• Experience in real estate, finance, logistics, or operations-heavy industries
• Evidence of research, technical publications, competitive programming, or open-source contributions

Technical Environment (Representative)

• Python and API-based architectures
• LLM platforms and agent orchestration frameworks
• Cloud infrastructure (AWS, Azure, or GCP)
• SQL and vector databases
• Workflow orchestration and automation tools
• Version control, logging, and monitoring systems

Success Metrics

• Performance in this role will be evaluated by:
• Reduction in manual administrative workload
• Automation coverage across operational workflows
• Accuracy and reliability of AI-driven outputs
• Adoption and usage across departments
• Operational efficiency gains and cost reductions

Work Environment

• Hybrid work model with in-person collaboration in Orange County
• Direct collaboration with executive leadership and operational teams
• High autonomy in system architecture and implementation decisions

Role:

Join project teams across the U.S. as the on-site catalyst who turns AI ideas into working reality. Partnering with each project’s AI Champion (Project Manager or Superintendent), you’ll uncover pain points, redesign workflows, and deploy AI agents that cut down reporting, accelerate RFIs, simplify lookahead planning, progress updates, materials tracking, and more. When needed, you will develop user stories and coordinate development with the central AI Studio. You’ll help advance the vision of the “Construction Site of the Future,” showing how agentic AI will transform project operations.

Location: New Haven, Connecticut

Responsibilities:

• Opportunity hunting and workflow redesign – Lead Lean/Six Sigma discovery workshops; map value streams, assess process and data maturity, and log low-effort/high-impact AI use cases.
• Process and data maturity assessment – Evaluate each jobsite’s current workflows and underlying data; surface gaps that block AI adoption and develop phased improvement plans with Operations Excellence to establish the right process baseline before deploying agents.
• Assess the market solutions – Evaluate off-the-shelf and platform tools; launch pilots, measure impact, and scale wins.
• Rapid AI-agent builds – Convert user stories into production-ready agents in Copilot Studio / Power Apps/Automate, ChatGPT Enterprise, or code-first frameworks within days; wire them to Teams/SharePoint on the front end and Databricks Lakehouse or other sources on the back end.
• Enterprise-grade engineering & LLMOps – Build RAG pipelines backed by Delta tables, Unity Catalog, and Databricks Vector Search; automate infra with GitHub Actions / Posit; monitor latency, cost, adoption, and drift.
• Data integrations – Partner with Data Engineering to design and maintain ETL pipelines, API integrations, and event-driven connectors feeding RAG and agents.
• Cross-cloud orchestration – Blend OpenAI, Azure OpenAI, and AWS Bedrock behind secure custom connectors; package agents for seamless rollout.
• Change enablement – Train crews, gather feedback, iterate, and track adoption and ROI metrics; apply influence model principles to embed agents into daily routines and SOPs, and track behavior change KPIs.
• Stakeholder communication – Brief project leadership and clients on agent impact in clear business terms; contribute use cases and playbooks for “Construction Site of the Future.”
• Escalation & hand-off – Draft clear user stories, data specs, and acceptance criteria for any complex solution that requires the central AI Solution Engineers or Data Engineering / Data Science team to lean in.

Qualifications:

• 3+ years in AI engineering / full-stack data applications or data science, including 2+ years building production LLM/RAG solutions.
• Bachelor’s in CS, Engineering, Physics, or a related field; Master’s preferred.
• Prior hands-on work in construction or heavy process industries (manufacturing, oil & gas, chemicals) is a significant plus.
• Demonstrated process excellence background (Lean/Six Sigma Green Belt or equivalent) with experience diagnosing process and data gaps and supporting change management plans with Operations Excellence.
• Strong facilitation and communication skills.
• Hands-on expertise with Copilot Studio, Power Apps/Automate, custom connectors, and CoE Toolkit governance.
• Programming & data stack: Python, SQL, Databricks Lakehouse, vector stores.
• DevOps & IaC: GitHub Actions (or Azure DevOps) and Posit Workbench/Connect automation or comparable CI/CD tooling; strong Git/GitHub workflow discipline.
• Integration & ETL skills: Foundational understanding of ETL/ELT design, Airflow or Databricks Workflows, and REST/GraphQL API development; proven collaboration with Data Engineering on source-to-lake and lake-to-agent pipelines.
• Willing and able to travel and work on active jobsites.

Why Zensar?

We’re a bunch of hardworking, fun-loving, people-oriented technology enthusiasts. We love what we do, and we’re passionate about helping our clients thrive in an increasingly complex digital world. Zensar is an organization focused on building relationships with our clients and with each other—and happiness is at the core of everything we do. In fact, we’re so into happiness that we’ve created a Global Happiness Council, and we send out a Happiness Survey to our employees each year. We’ve learned that employee happiness requires more than a competitive paycheck, and our employee value proposition—grow, own, achieve, learn (GOAL)—lays out the core opportunities we seek to foster for every employee. Teamwork and collaboration are critical to Zensar’s mission and success, and our teams work on a diverse and challenging mix of technologies across a broad industry spectrum. These industries include banking and financial services, high-tech and manufacturing, healthcare, insurance, retail, and consumer services. Our employees enjoy flexible work arrangements and a competitive benefits package, including medical, dental, vision, 401(k), among other benefits. If you are looking for a place to have an immediate impact, to grow and contribute, where we work hard, play hard, and support each other, consider joining team Zensar!

QA / Quality Engineering Delivery Lead

Location: Secaucus, NJ (Hybrid – 3 days onsite)

Employment Type: Full-time / Contract

Experience: 12–15 years

Domain: Retail

Role Overview

We are seeking a QA / Quality Engineering Delivery Lead to own end-to-end quality delivery while driving QE transformation and modernization initiatives, including AI-augmented testing and intelligent automation frameworks. This role demands a tool-agnostic automation mindset, strong leadership capabilities, and the ability to balance BAU delivery with future-ready QE transformation, leveraging GPT-based testing and AI-led quality practices.

Key Responsibilities:

• Own quality outcomes across programs, releases, and product lines
• Lead day-to-day BAU QA delivery, including:
• Test planning & execution
• Defect management
• Release validation and go/no-go readiness
• Drive QE assessments and build continuous improvement & transformation roadmaps
• Define and execute modern test automation strategies across:
• UI, API, Mobile, and End-to-End (E2E) automation
• Lead AI-augmented testing initiatives, including:
• GPT/LLM-based test case generation
• Intelligent test design and risk-based testing
• Self-healing automation and test optimization
• Promote shift-left and shift-right testing by partnering with:
• Product Management
• Engineering
• DevOps and SRE teams
• Embed quality early in the SDLC through CI/CD and cloud-native testing
• Establish and track quality metrics, KPIs, and dashboards
• Provide clear visibility into quality status, risks, and dependencies for senior stakeholders
• Mentor QA/QE teams and foster a continuous improvement and innovation culture.

Required Skills & Experience

Must Have

• 10–14 years of experience in QA / Quality Engineering
• Proven leadership experience managing QA/QE teams in Agile & DevOps environments
• Strong hands-on expertise in test automation frameworks, including:
• Selenium, Playwright, Cypress (any one or more)
• Exposure to Tricentis Tosca (preferred but not mandatory)
• Solid experience in:
• API & integration testing
• Test data management
• Defect lifecycle management
• Demonstrated experience conducting:
• QE maturity assessments
• Automation ROI analysis
• QE transformation planning
• Ability to manage BAU delivery alongside modernization and innovation initiatives
• Strong Retail domain experience (POS, eCommerce, supply chain, merchandising systems preferred)

AI-Augmented & Intelligent QE (Mandatory Focus)

• Hands-on or leadership experience with AI-driven QE practices, including:
• GPT / LLM-based test case & test scenario generation
• AI-assisted exploratory testing
• Intelligent test selection, prioritization, and impact analysis
• Experience building or adopting intelligent automation frameworks with:
• Self-healing capabilities
• Dynamic locators & adaptive scripts
• Familiarity with:
• Generative AI usage in QE pipelines
• Prompt engineering for test generation
• Ability to operationalize AI in QE, not just PoCs

Zensar believes that diversity of backgrounds, thought, experience, and expertise fosters the robust exchange of ideas that enables the highest quality collaboration and work product. Zensar is an equal opportunity employer. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Zensar is committed to providing veteran employment opportunities to our service men and women. Zensar is committed to providing equal employment opportunities for people with disabilities or religious observances, including reasonable accommodation when needed. Accommodation made to facilitate the recruiting process are not a guarantee of future or continued accommodation once hired.

All applicants must be legally authorized to work with Zensar. Visa sponsorship may be available for qualified applicants for certain positions.

Zensar values your privacy. We’ll use your data in accordance with our privacy statement located at: