Tavus, AI Jobs in Usa

Voxology is redefining patient engagement with AI-driven solutions designed to streamline healthcare access and administrative processes. Our mission is to enable healthcare providers to deliver effortless, patient-centric experiences.

Through advanced conversational AI, we power seamless communication across voice, text, and chat—reducing wait times, improving access, and enhancing the overall patient experience. By integrating with leading EMRs, we simplify the end-to-end patient journey, from scheduling and intake to financial clearance and follow-up, allowing providers to focus on delivering exceptional care.

We’re looking for a healthcare front office professional to help improve the quality and accuracy of AI-driven patient interactions.

This is a part-time (5–10 hrs/week), remote role where you’ll review real patient calls, identify issues, and help refine how AI agents handle scheduling, intake, and patient communication.

If you’ve worked at a front desk, call center, or in patient access, this is a great opportunity to get exposure to AI while leveraging your real-world experience.

• Listen to recorded patient calls and review transcripts
• Identify issues in conversations (missed scheduling opportunities, incorrect responses, confusing workflows)
• Provide clear, actionable feedback on what should have happened instead
• Tag and label conversations (patient intent, outcomes, error types)
• Ensure AI workflows align with real-world front office processes
• Identify patterns and recurring issues across interactions

• 1+ year experience in a healthcare front office role, such as:
• Patient Access Representative
• Medical Receptionist
• Scheduling Coordinator
• Healthcare Call Center Agent
• Strong attention to detail
• Comfortable reviewing calls/transcripts and providing structured feedback
• Understand how real patient conversations and workflows operate

• Experience with EMRs (Athena, NextGen, Epic, etc.)
• Exposure to scheduling, insurance verification, or referral workflows
• Prior QA, auditing, or call review experience

• Work on real-world AI used by healthcare providers
• Directly impact patient experience and access to care
• Flexible, part-time schedule
• Strong entry point into healthcare + AI

• Location: Remote
• Time Commitment: 5–10 hours per week
• Compensation: $20–$40/hour (based on experience)

Location: Anywhere in Country

At EY, we’re all in to shape your future with confidence.

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.

AI & Data - AI Strategy - Senior Manager - Oil & Gas Sector

As part of our growing AI & Data practice, we are seeking a highly experienced Senior Manager to lead enterprise AI strategy and quantitative modeling efforts for our clients in the Oil & Gas sector. This individual will bring deep industry expertise, along with a proven track record of designing and operationalizing responsible, scalable, and value-aligned AI solutions. You’ll lead high-impact client engagements focused on Generative AI, Agentic AI, MLOps, and AI governance frameworks — driving measurable outcomes in upstream, midstream, and downstream operations.

As a Senior Manager in AI Strategy, you will leverage proprietary, industry-aligned business models and innovative operating model designs to deliver impactful AI investments. You will be responsible for capability assessments, operating model design, product management, governance, and process design, ensuring that AI initiatives align with business strategies and stakeholder needs.

In this role, you will lead the delivery of complex AI strategies that enhance business effectiveness and efficiency. You will work closely with clients to envision how AI can transform their markets, products, and capabilities. This position offers the opportunity to engage with business and technology leaders, driving strategic programs that significantly impact their operations.

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• Lead engagement delivery, ensuring quality and risk management throughout the project lifecycle.
  
• Manage client relationships, focusing on revenue generation and the identification of new opportunities.
  
• Develop and manage resource plans and budgets for engagements, ensuring alignment with performance objectives.
  
• Define and implement enterprise-wide AI and quantitative modeling strategy tailored to oil & gas value chains (e.g., asset optimization, drilling, trading, predictive maintenance).
  
• Establish AI governance frameworks that ensure responsible AI adoption, ethical use of data, model risk management, and alignment with evolving regulations.
  
• Design and operationalize Agentic AI solutions to automate reasoning, planning, and decision‑making tasks in complex environments.
  
• Drive the prioritization of AI use cases based on business value, feasibility, and risk, ensuring ROI on AI initiatives.
  
• Lead multidisciplinary teams of data scientists, engineers, and consultants to deliver end‑to‑end AI platforms and solutions.
  
• Partner with senior business and IT leaders to identify strategic opportunities and shape AI‑enabled business transformation.
  
• Implement and scale ModelOps and MLOps practices, ensuring transparency, reproducibility, and monitoring of models in production.
  
• Lead AI solution architecture, including hybrid deployments on cloud (e.g. Microsoft Azure, Amazon AWS).
  
• Serve as a thought leader in emerging AI technologies, including Generative AI, foundation models, RAG and Agentic AI.
  
• Drive internal capability building and innovation in Responsible AI, agentic workflows, and energy sector‑specific solutions.
  

To excel in this role, you will need a blend of technical and interpersonal skills. Your ability to navigate complex challenges and deliver innovative solutions will be crucial.

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• Strong analytical and decision‑making skills to develop solutions to complex problems.
  
• Proven experience in managing client relationships and leading teams.
  
• Ability to communicate effectively and influence stakeholders at all levels.
  

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• Bachelor’s degree required; Master’s degree preferred with focus in Computer Science, Applied Math, or related field with prior consulting experience required.
  
• 10+ years of experience in technology consulting, digital transformation, or AI‑driven business solutions.
  
• 5+ years of leadership in AI/ML projects, including team management and executive stakeholder engagement.
  
• Typically, no less than 5 — 7 years of relevant experience.
  
• Strong expertise in AI Platforms and Tools.
  
• Proficiency in Data Architecture Design and Modelling.
  
• Experience in Digital Transformation and IT Effectiveness Assessment.
  
• Knowledge of Emerging Technologies and Technology Strategy, Vision, and Roadmap.
  
• Ability to build and manage relationships effectively.
  
• Strong exposure to oil & gas industry operations, value levers, and use case landscape.
  
• Proven success in developing AI strategy and governance models, including frameworks for Responsible AI, risk, and compliance.
  
• Hands‑on experience with Generative AI frameworks (e.g., OpenAI, Hugging Face, LangChain, RAG).
  
• Experience architecting and scaling MLOps platforms and data science workflows in cloud‑native environments.
  
• Proficiency in Python and tools like Pandas, PyTorch, Scikit‑learn, Spark, SQL.
  
• Experience with CI/CD, containerization (e.g., Docker, Kubernetes), and MLFlow or similar tools.
  
• Strong client‑facing skills with the ability to articulate technical topics to business executives.
  

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• Experience in managing change and leading teams.
  
• Strong negotiation and influencing skills.
  
• Familiarity with sector knowledge and commercial acumen.
  
• Prior experience leading AI initiatives in the energy or oil & gas sector, including exploration, refining, or energy trading.
  
• Familiarity with agentic AI concepts, cognitive architectures, and autonomous agents.
  
• Working knowledge of ESG data, climate risk modeling, and regulatory trends in energy.
  
• AI certifications (Microsoft, AWS, NVIDIA, Databricks, or equivalent).
  
• Exposure to agile delivery models and design thinking approaches.
  

We seek individuals who are not only skilled but also passionate about driving innovation and transformation through AI. Top performers are those who can think critically, solve complex problems, and communicate effectively with diverse stakeholders. If you are eager to make a significant impact and thrive in a collaborative environment, we want to hear from you!

At EY, we’ll develop you with future‑focused skills and equip you with world‑class experiences. We’ll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more.

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  We offer a comprehensive compensation and benefits package where you’ll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job in all geographic locations in the US is $144,000 to $329,100. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $172,800 to $374,000. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.

  
  
  
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  Join us in our team‑led and leader‑enabled hybrid model. Our expectation is for most people in external, client‑serving roles to work together in person 40‑60% of the time over the course of an engagement, project or year.

  
  
  
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  Under our flexible vacation policy, you’ll decide how much vacation time you need based on your own personal circumstances. You’ll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well‑being.

  
  
  

Are you ready to shape your future with confidence? Apply today.

EY accepts applications for this position on an on‑going basis.

For those living in California, please click here for additional information.

EY focuses on high‑ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities.

EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law.

EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1‑800‑EY‑HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY’s Talent Shared Services Team (TSS) or email the TSS at .

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.

** We will only consider applicants who are currently residing in South Florida**

About MMG

MMG Equity Partners is a Miami-based, family-led real estate investment and development platform with a portfolio of retail shopping centers across South Florida. Beyond the real estate business, MMG operates a private family office that manages investments, insurance, and financial reporting across multiple entities and family members. MMG separately owns Tamarack Resort in Idaho. We are a flat, fast-moving organization where you will work directly with principals — not layers of management.

This is a ground-floor role. We are building the function from scratch. The right person will define what AI means at MMG, then build it.

The Role

The Director of AI Initiatives & Adoption is responsible for identifying, implementing, and managing AI tools and systems that meaningfully improve how MMG operates across real estate and family office functions. Every project you take on must connect to a business outcome — faster decisions, better data, more deals, reduced overhead.

You will own four things: identifying where AI creates real value at MMG, building or procuring the tools to capture that value, driving adoption across the team and continuously improving how those tools are used, and ensuring the systems are secure and maintainable. Implementation without adoption is not success.

• Reports to Managing Director
• Direct reports - contractors and freelancers as needed
• Current IT Enviroment - outsourced IT for network support

Current Tech Stack (what you are walking into)

You need to understand these systems deeply. Part of your job is figuring out how to connect them and leverage AI to make us more productive/competitive

What you will work on

Below are four areas where we believe AI creates the nearest near-term value at MMG. You first job is to work with the leaders in each area to assess each, prioritize, and build a 6-month roadmap. In addition to the below, the right individual will identify a myriad of other AI use cases to add value and reduce repetitive tasks.

1. Leasing and Tenant Prospecting

MMG owns retail shopping centers and is responsible for filling vacancies with the right tenants – while we work with third party leasing firms, we wish to supplement their efforts by generating direct leads.

• Design and build AI scraping tools to compile databases of South Florida retailers and service businesses for targeted uses
• Build a tool to identify prospective uses/tenants: given a vacancy (size, location, co-tenancy, demographics), which business types and specific operators are the best candidates?
• Design and build AI-assisted leasing outreach workflow: targeted uses identified for vacancies → database queried → outreach drafted and sent → responses tracked in Dynamics (or other CRM)
• Activate Microsoft Dynamics (or other) as the CRM for online leasing
• Identify tools or workflows to monitor existing tenant health (sales reporting, foot traffic, business review signals) to get ahead of vacancies before they happen
• Identify and implement AI-assisted lease abstracting tool to best fit our environment

2. Real Estate Acquisitions

MMG evaluates potential acquisitions across South Florida. Today this process is manual and dependent on individual knowledge. AI can accelerate every stage.

• Design and build AI scraping tools to compile databases of South Florida real estate owners
• Build an AI-assisted underwriting workflow that pulls property data, comps, and market context into a structured analysis template
• Identify AI tools for market intelligence — rent growth trends, cap rate movements, retail category performance by submarket
• Evaluate AI-powered deal sourcing tools (e.g. CoStar integrations, off-market sourcing platforms

3. Private Family Office

MMG's family office manages investments, insurance, and financial reporting for family members. This is a sensitive area requiring strict data governance — but it also has high-value AI applications.

• Addepar AI integration: explore ways to use AI to generate plain-language investment performance summaries and financial reports from Addepar data, reducing manual reporting time
• Insurance management: build a structured database or AI assistant for tracking insurance policies (G/L, personal property, family member policies) with renewal alerts and coverage gap analysis
• Document intelligence: connect family office files in SharePoint to an AI interface for on-demand retrieval of partnership agreements, tax documents, and legal filings
• Evaluate data governance and access controls for family office data — this is sensitive personal and financial information; AI access must be role-based and audited

IT Infrastructure and Security

You are not a network administrator — we have an outsourced IT firm for that. But you are responsible for AI governance at MMG: ensuring every AI tool introduced into the environment meets a clear security and accountability standard.  Practically, this means:

• Evaluating AI vendors for data handling practices — what data leaves our environment, where it is stored, and how it is used for model training
• Defining and enforcing a data classification policy: what information can be sent to external AI APIs, what must stay on-premise or in private cloud environments
• Working with IT firm to ensure AI tools are deployed within the MS365/Azure security perimeter where possible
• Evaluating the Claude Teams → Claude Enterprise migration and the Microsoft Connector configuration for SharePoint access — specifically, controlling which documents are accessible to AI and by which users
• Vetting any third-party AI integrations (i.e. ZoomInfo, Yardi, etc.) for compliance with firm data policies

Prompt Library & AI Adoption

Building the tools is only half the job. The other half is making sure the team actually uses them — and uses them well. This requires two ongoing responsibilities that most AI roles underestimate.

Prompt Library

You will build and maintain a living prompt library — a curated set of tested, optimized prompts for every recurring AI task at MMG. Examples include: underwriting analysis from a rent roll, lease abstraction for a specific clause type, tenant outreach drafts by use category, and insurance renewal gap analysis. The library lives in SharePoint, is accessible to the full team, and is updated continuously based on user feedback and evolving business needs. A well-maintained prompt library is what turns AI from a tool that one person uses well into a capability that the whole organization depends on.

Adoption Monitoring & Continuous Improvement

You are responsible for whether AI tools actually get used — not just whether they get deployed. This means tracking adoption across the team, identifying where workflows are not sticking, providing training and troubleshooting support to staff using AI tools, and iterating on both the tools and the prompts based on real usage patterns. You will serve as the primary internal resource for the team when they hit limitations or need guidance on how to get better outputs. Deployment without adoption is a sunk cost.

What we are looking for

Required:

• 3–6 years of experience in data, technology, or AI — ideally in a context where you had to figure things out without a large team around you
• Hands-on experience with AI tools and LLM platforms — not just using them, but building workflows, prompts, and integrations on top of them
• Demonstrated ability to connect AI capabilities to specific business outcomes (not just technology for its own sake)
• Comfort with the Microsoft 365 ecosystem — SharePoint, Dynamics, Teams, Azure
• Ability to manage and direct contractors and developers without being the one writing all the code
• Non-technical stakeholder communication — you will regularly present AI recommendations, tool evaluations, and implementation roadmaps directly to the principal(s) who are real estate operators, not technologists. The ability to translate AI capabilities into business outcomes (not feature lists) is non-negotiable. If you cannot explain why a tool matters in terms of time saved, deals sourced, or risk avoided, you will not be effective in this role
• In-office presence at Pinecrest HQ is required initially (possible hybrid in the future)

Preferred

• Experience in commercial real estate, property management, or a related field
• Familiarity with Yardi, Addepar, or similar platforms
• Background that includes both technical work (building things) and strategic work (recommending what to build)
• Experience implementing AI in a small-team / resource-constrained environment

GENERAL SUMMARY:

The Manager of AI Enablement (Senior) leads the development and execution of Element Care’s internal approach to artificial intelligence. This role defines AI standards, policies, and best practices while enabling staff across the organization to adopt AI safely, ethically, and effectively. Reporting to the IT department, this position acts as a trusted advisor to leaders and end users, shaping AI governance, vendor strategy, training, and enterprise enablement.

ESSENTIAL RESPONSIBILITIES:

•    Define and maintain organizational AI standards, policies, and governance frameworks.

•    Lead the deployment of off-the-shelf AI solutions, including ambient documentation, predictive analytics, administrative automation, and clinical decision support tools.

•    Enable responsible use of generative AI across administrative and operational functions.

•    Conduct continuous workflow analysis to identify automation and AI-enablement opportunities.

•    Evaluate AI and AI/ML models, tools, and vendor solutions for suitability, risk, and value.

•    Partner with IT, data, analytics, and platform teams to align AI initiatives with enterprise architecture.

•    Provide oversight and guidance on AI-enabled workflows, automation, and agent capabilities.

•    Measure, monitor, and report on AI initiative outcomes, value realization, and performance.

•    Build business cases and recommendations for future AI investments.

•    Serve as the primary advisor to leaders and teams on AI use cases, risks, and governance.

•    Monitor regulatory, ethical, and industry developments related to AI.

•    Help establish and mature a scalable AI enablement and governance operating model.

•    Influence adoption and consistency without direct authority.

•    Perform other duties as assigned.

JOB SPECIFICATION:

•    6–10+ years of relevant professional experience, including applied AI, automation, analytics, or emerging technology leadership.

•    Demonstrated experience evaluating AI/ML models, vendor solutions, or AI platforms.

•    Experience with vendor management, solution selection, or hands-on implementation required.

•    Demonstrated experience defining standards, policies, or enterprise enablement programs.

•    Healthcare or other regulated industry experience strongly preferred.

•    Strong understanding of applied AI, AI/ML evaluation, governance, risk, and ethical considerations.

•    Ability to translate complex concepts into practical organizational guidance.

•    Experience developing business cases and value narratives for technology investments.

•    Executive-level communication and facilitation skills.

•    Proven ability to operate independently and influence across the enterprise.

•    Strategic mindset with a pragmatic, implementation-oriented approach.

Compensation details: 13 Yearly Salary

PI71b2d5685c13-3631

Hands-On Product Manager — AI-Native Recruiting Platform (HireHQ)

Build the AI operating system for recruiting.

HireHQ is building the next generation AI-native recruiting platform — one that eliminates manual recruiter workflows and replaces them with intelligent automation, AI copilots, and decision intelligence.

Traditional ATS platforms were built for record keeping.

HireHQ is building a recruiting operating system that helps companies find, evaluate, and hire the best talent faster.

We are looking for a highly hands-on Product Manager who can help design and ship this future.

This is not a traditional PM role. You won’t just write tickets and manage roadmaps.

You will:

• Prototype product ideas yourself
• Use AI tools to rapidly build concepts
• Work directly with engineers
• Drive automation across recruiting workflows
• Ship AI-native features quickly

If you like building products at the intersection of AI, automation, and recruiting, you’ll thrive here.

What You'll Work On

You’ll help build core capabilities of the HireHQ recruiting platform, including:

AI Candidate Discovery

• AI-powered candidate search
• Intelligent candidate matching
• Automated candidate enrichment
• Talent graph and candidate insights

AI Screening & Evaluation

• Resume and profile understanding
• AI candidate scoring and ranking
• Interview intelligence and summarization
• Automated screening workflows

Recruiter Copilots

• AI recruiter assistants
• Automated outreach generation
• Pipeline prioritization
• Smart next-action recommendations

Candidate Experience

• AI-powered communication
• Automated follow-ups
• Interview scheduling automation
• Candidate journey insights

Recruiting Automation

• Workflow orchestration across the hiring pipeline
• Intelligent routing and task automation
• AI-driven pipeline management
• Recruiter productivity tools

Our goal is simple:

Reduce manual recruiting work by 80% while improving hiring outcomes.

What You'll Actually Do

You will operate like a product builder.

Ship Products

• Own product areas end-to-end
• Work directly with engineers to design solutions
• Move from idea → prototype → shipped feature quickly

Prototype With AI

You’ll actively use tools like:

• Cursor
• GitHub Copilot
• Claude
• ChatGPT
• Figma

to rapidly create:

• product mockups
• workflows
• prototypes
• PRDs
• user stories
• experimentation plans

We expect PMs to use AI as a force multiplier, not just write docs.

Design AI-Native Workflows

You'll help design product systems that use:

• LLMs
• semantic search
• embeddings
• candidate matching
• summarization
• automation engines

to eliminate manual recruiting work.

Drive Automation

You will constantly ask:

"Why is a human doing this?"

Then build systems that automate it.

Work Extremely Closely With Engineering

You will collaborate daily with engineers to:

• shape product architecture
• refine technical tradeoffs
• ship features quickly
• iterate with real customer feedback

What We're Looking For

Experience

• 5+ years in product management
• Experience building recruiting or HR tech products

Examples include:

• Applicant Tracking Systems (ATS)
• Recruiting CRM platforms
• Candidate engagement tools
• Talent sourcing platforms
• Interview platforms
• Talent intelligence platforms

You deeply understand how recruiting actually works.

AI Product Thinking

You’ve helped build or design AI-enabled product capabilities, such as:

• candidate matching
• screening automation
• workflow automation
• recommendation systems
• AI copilots
• search and ranking systems

Builder Mindset

You like creating things, not just planning them.

You are comfortable:

• prototyping ideas
• creating workflows
• building product concepts independently
• using AI tools to accelerate execution

Comfort With Ambiguity

This is a startup environment.

You should enjoy:

• fast iteration
• unclear problems
• ownership
• shipping quickly

Strong Candidates Often

• Previously worked at HR tech or recruiting tech companies
• Have built ATS or recruiting workflow products
• Use AI tools daily for product development
• Think about automation and workflow intelligence
• Care deeply about shipping useful products quickly

What Success Looks Like

Within your first 3 months:

• Recruiters using HireHQ spend dramatically less time on manual tasks
• AI features automate key recruiting workflows
• Customers rely on AI insights to prioritize candidates
• Recruiters move from administrative work → strategic hiring

Why This Role Is Different

Most recruiting software was designed 15–20 years ago.

HireHQ is rebuilding recruiting software from the ground up using:

• AI agents
• workflow automation
• intelligent candidate matching
• recruiter copilots

This role is an opportunity to help build the AI operating system for hiring.

Director of AI

Location: Chicago, IL (Remote Eligible – must be US based)

Salary: $250,000 – 280,000 base + bonus

We’re partnering with a global education technology company undergoing a major transformation from a traditional publisher into a data and AI driven digital learning platform. The organization is investing heavily in AI and advanced data capabilities to deliver personalized learning experiences at global scale.

They are hiring a Director of AI to lead a team of AI researchers and data scientists responsible for developing and deploying advanced machine learning and Generative AI solutions across the enterprise.

The Role:

This is a highly strategic role that combines technical leadership, team management, and hands-on architectural oversight. The Director of AI will help define the long-term AI roadmap while working closely with product, engineering, and business stakeholders to bring production AI systems to life.

What you’ll do:

• Lead and grow a team of AI researchers and data scientists, providing technical mentorship and career development
• Define and execute the AI strategy and roadmap, with a strong focus on Generative AI capabilities
• Partner with product, engineering, and business teams to identify high-impact AI opportunities
• Oversee the design, development, and deployment of production-grade AI and ML systems
• Translate complex technical work into clear insights for both technical and executive stakeholders
• Manage project timelines, priorities, and team resources to ensure successful delivery of AI initiatives

What They’re Looking For

• PhD in Artificial Intelligence, Data Science, Computer Science, or a related technical field
• 8+ years of experience in AI, machine learning, or data science
• Proven experience leading teams of AI researchers or data scientists
• Deep expertise in machine learning, AI systems, and Generative AI technologies
• Strong communication skills with the ability to present technical concepts to senior leadership
• Experience collaborating cross-functionally with product, engineering, and business teams

Nice to Have

• Experience deploying Generative AI solutions in production environments
• Experience working in large-scale technology or digital product organizations
• Exposure to education technology or learning platforms

This role offers the opportunity to shape the AI strategy for a global platform impacting millions of learners worldwide, while leading a highly technical team working on cutting-edge machine learning systems.

Senior Business Analyst Life & Annuities

Onsite in WDM office 4 days a week

Contract

Overview:

We are seeking an experienced Senior Business Systems Analyst (AI Enablement) to support ***’s AI transformation initiatives. This role will partner with ***’s BSA team, IT leadership, and PMO to understand current SDLC processes, identify pain points, gaps, and inconsistencies across teams, and translate findings into a more streamlined, AI-enabled operating model.

The BSA will assess our current requirements elicitation process and help define how an AI-infused approach can significantly improve the thoroughness, completeness, and quality of user requirements specifically for consumption by an AI coding agent. This includes identifying cross-system dependencies, non-functional requirements, and user personas from initial requirement elicitation through Jira story creation. This role will help transform our BSA capabilities by leveraging custom-built AI solutions to accelerate cycle time, improve consistency, and reduce downstream rework.

This role will also define measurable success criteria and develop metrics to evaluate process improvements and AI impact across the SDLC: gathering requirements across several other SDLC-related AI initiatives and provide light project management support across multiple AI workstreams.

Key Responsibilities

Assess current BA workflows, documentation standards, and impact analysis processes from user requirement elicitation through Jira story creation, identifying gaps, redundancies, inconsistencies and improvements across teams.

Identify friction points and define AI-enabled use cases with measurable business outcomes.

Drive feedback loops for AI proofs of concept (POCs) delivered to teams by gathering structured user input, measuring adoption and effectiveness, and incorporating insights into iterative improvements.

Develop clear, actionable requirements including user stories, acceptance criteria, non-functional requirements, personas, and upstream/downstream system impacts.

Determine and help establish processes or patterns to ensure user requirements align with current system capabilities. Proactively identify cross-system dependencies, technical constraints, gaps, and system limitations in collaboration with engineering teams to ensure requirements are technically feasible and implementation-ready.

Support backlog grooming, sprint planning, demos, and pilot validation sessions.

Track progress across multiple AI initiatives, manage dependencies and risks, and maintain clear stakeholder communication.

Develop and maintain lightweight project plans, timelines, and status reporting to ensure AI initiatives remain aligned with business priorities and strategic objectives.

Required Qualifications

5+ years of Business Analysis or Business Systems Analysis experience in technology or software environments.

Strong requirements elicitation, documentation, and facilitation skills.

Experience working in Agile environments with cross-functional teams.

Practical familiarity with AI tools (e.g., Claude Code CLI, ChatGPT, Copilot) and understanding of AI concepts (LLMs, prompt engineering, AI governance, and AI risk considerations).

Strong systems thinking, structured communication, and stakeholder management skills.

Preferred Experience

Experience implementing AI or automation solutions within enterprise environments.

Familiarity with AWS AI services (e.g., AWS Bedrock) or other enterprise AI platforms.

Familiarity with Jira, Confluence, GitHub, or similar SDLC ecosystems.

Experience supporting PMO processes or managing multiple concurrent initiatives along with a functional understanding of Agile practices.

Financial services or insurance industry experience.

Success Measures

Successful delivery of an AI-enabled solution for ***’s BSA team.

Improved BA workflow efficiency, quality, and consistency.

High-quality, implementation-ready requirements that reduce downstream rework and delivery thrash.

Effective coordination, transparency, and measurable progress across AI initiatives.

Be a part of our success story. Launch offers talented and motivated people the opportunity to do the best work of their lives in a dynamic and growing company. Through competitive salaries, outstanding benefits, internal advancement opportunities, and recognized community involvement, you will have the chance to create a career you can be proud of. Your new trajectory starts here at Launch!

The Role:

Launch is actively seeking a visionary Solutions Architect / Principal Software Engineering Lead (AI) to design and deliver modern engineering and applied AI solutions across client engagements. This role blends deep hands‑on engineering, architectural leadership, AI system design, and client advisory. You will operate across system design, production‑grade engineering, multi‑agent architectures, cloud platform strategy, and the development of Launch’s AI practice.

Responsibilities Include:

Architecture & Technical Strategy

• Define the technical direction for client engagements end-to-end: discovery, design, build, and production hardening.
• Assess client technology ecosystems and identify high-impact opportunities for AI/ML integration.
• Lead architecture reviews, design sessions, and technology selection across cross-functional stakeholder groups.
• Translate ambiguous business problems into concrete engineering plans with clear scope, milestones, and risk callouts.

AI Engineering & Delivery

• Architect production agentic systems including multi-agent orchestration, agent harnesses, skill/tool composition, human-in-the-loop checkpoints, and inter-agent communication protocols (e.g., A2A, MCP).
• Build and govern MCP server ecosystems: design, deploy, and secure Model Context Protocol integrations connecting AI agents to enterprise data sources, internal APIs, and third-party platforms.
• Define agent skill and capability frameworks including reusable skill libraries, prompt engineering standards, and evaluation harnesses for consistent agent behavior across engagements.
• Architect RAG pipelines, fine-tuning workflows, and model lifecycle infrastructure (training, serving, experiment tracking) as foundational components of agentic systems.
• Integrate AI platforms and APIs (Azure OpenAI, Amazon Bedrock, Anthropic, Vertex AI) into production systems with enterprise-grade reliability, cost governance, and observability.
• Establish AI-native development practices: embed tools such as Claude Code, Cursor, and GitHub Copilot into team workflows with standards for AI-assisted code review, test generation, and documentation.
• Design evaluation and observability infrastructure including LLM eval frameworks, red-teaming, behavioral drift detection, and production monitoring across tool call chains, latency, and failure modes.
• Apply responsible AI governance: define guardrails, access controls, and audit patterns for agentic workflows in enterprise environments including scope containment and escalation paths.

Hands-On Engineering

• Write production code and lead by example — this role requires someone who is still close to the code.
• Design cloud-native architectures across multiple hyperscalers (AWS and Azure primarily) microservices, event-driven systems, serverless, and containerized workloads.
• Define and implement infrastructure-as-code using tools such as Terraform, Pulumi, CloudFormation, or Bicep.
• Design and optimize CI/CD pipelines, GitOps workflows, and container orchestration using Docker and Kubernetes.
• Establish observability and reliability practices using tools such as Datadog, Prometheus, Grafana, CloudWatch, or Azure Monitor.
• Drive security-by-design across the delivery lifecycle including IAM, network architecture, secrets management, and compliance automation.

Leadership & Client Advisory

• Lead engineering teams ranging from small squads to 10+ person delivery teams, scaling leadership approach to the needs of each engagement.
• Mentor and develop engineers at all levels through code reviews, pairing, and design coaching.
• Operate as a trusted advisor to client technical leadership and executive stakeholders. Communicate trade-offs clearly and build confidence.
• Influence without direct authority — driving alignment across cross-functional teams through technical credibility and stakeholder management.
• Lead discovery and requirements elicitation, surfacing the underlying business need beyond the stated request.
• Produce clear written artifacts: technical proposals, architecture decision records, SOWs, and executive-level status communication.
• Grow client relationships and identify follow-on opportunities through proposal contributions and delivery-driven account expansion.
• Contribute to Launch's growth — practice development, thought leadership, and hiring.

Qualifications:

Must-Haves:

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
• 10+ years in software engineering with demonstrated experience in architecture and technical leadership roles.
• 3+ years hands-on with AI/ML in production. Broad fluency across generative AI (LLMs, RAG, fine-tuning, agents), MLOps (model serving, pipelines, experiment tracking), and AI-integrated product development.
• Consulting or client-facing delivery experience with a proven ability to integrate into client organizations and establish credibility with technical and executive stakeholders.
• Full-stack engineering capability across frontend, backend, infrastructure, and data layers. Proficiency in multiple modern languages (e.g., Python, TypeScript/Node.js, C#/.NET, Java, or Go) with the ability to move between them as engagements require.
• Multi-hyperscaler depth across AWS and Azure, including their respective AI/ML service ecosystems (Bedrock, SageMaker, Azure OpenAI, Azure ML). GCP experience is a plus.
• Strong fundamentals in distributed systems, event-driven architecture, API design, and DevOps/platform engineering.
• Experience leading engineering teams in agile delivery environments.
• Business acumen with the ability to connect architecture decisions to cost, timeline, and organizational impact.
• Executive presence and communication skills effective with both technical and non-technical audiences.
• Proven ability to operate in ambiguous environments and adapt to diverse client cultures.

Strong Differentiators

• Experience contributing to the development of AI engineering practices, reusable frameworks, or internal accelerators within a consulting or enterprise environment.
• Experience advising C-suite or VP-level stakeholders on AI strategy, investment prioritization, and organizational readiness.
• Depth with agentic AI frameworks (LangChain, LangGraph, LangSmith, LlamaIndex, Semantic Kernel, CrewAI) and emerging standards like MCP (Model Context Protocol).
• Experience with enterprise data platforms (Databricks, Snowflake, BigQuery) in the context of AI/ML workloads.
• Cloud architecture certifications across AWS and Azure (AWS SA Professional, Azure Solutions Architect Expert).
• Published writing, open-source contributions, or conference speaking that demonstrates thought leadership in AI or software architecture.
• Domain depth in industries such as healthcare, financial services, retail, or public sector.

Compensation & Benefits:

As an employee at Launch, you will grow your skills and experience through a variety of exciting project work (across industries and technologies) with some of the top companies in the world! Our employees receive full benefits—medical, dental, vision, short-term disability, long-term disability, life insurance, and matched 401k. We also have an uncapped, take-what-you-need PTO policy. The anticipated base wage range for this role is $190,000 to $230,000. Education and experience will be highly considered, and we are happy to discuss your wage expectations in more detail throughout our internal interview process.

• 
  
• A typical day will involve a mix of hands-on coding, architectural design, and research.
  
• The engineer will spend a significant portion of their time in Python, building and optimizing agentic AI systems using frameworks like LangChain.
  
• This includes integrating these agents with our backend services and deploying them using CI/CD pipelines into our cloud environment.
  
• They will also be responsible for researching and testing new agentic models and frameworks, monitoring agent behavior in production, and collaborating with data scientists and business stakeholders to refine requirements and ensure the ethical deployment of AI solutions.
  

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• Python
  
• JavaScript/TypeScript
  
• AI Tools and Libraries (e.g. LangGraph, LangChain, Deep Agents, Claude Skills, etc.)
  
• AI Models (e.g. Claude, OpenAI, etc.)
  
• AI Concepts (e.g. Prompt Engineering, RAG, Agentic AI, etc.)
  
• Distributed SDLC/DevOps (e.g. github, pipelines, VS Code, testing frameworks, etc.)
  
• Platforms (Container Platforms, Cloud Platforms, Document Databases, AWS)
  
• API Design
  

• 
  
• Deep hands-on experience in Python for AI/ML development.
  

• 
  
• Generative AI Development: Proven experience developing Gen AI or AI/ML solutions, from use case conceptualization to production deployment.
  
• Infrastructure & DevOps: Strong understanding of cloud environments (AWS preferred), LLM hosting, CI/CD pipelines, Docker, and Kubernetes.
  
• Agentic AI Concepts: Knowledge of agentic/autonomous systems (e.g., reasoning, planning, tool use).
  

• 
  
• Proficiency in Python development and FastAPI/Flask frameworks, along with SQL.
  
• Familiarity with agentic AI frameworks and concepts such as LangChain, LangGraph, AutoGen, Model Context Protocol (MCP), Chain of Thought prompting, knowledge stores, and embeddings.
  
• Experience developing autonomous agents using cloud-based AI services.
  
• Experience with prompt engineering techniques and model fine-tuning.
  
• Strong understanding of reinforcement learning, planning algorithms, and multi-agent systems.
  
• Experience working across cloud platforms (AWS, Azure, GCP) and deploying AI solutions at scale.