Backops, AI Jobs in Usa

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.

Key Responsibilities:

• Design and deploy observability frameworks leveraging tools such as Grafana, Dynatrace, Prometheus, ELK, Splunk, etc. Define best practices for monitoring, alerting, and visualization across hybrid and multi-cloud environments.
• Develop strategies for monitoring KPIs tied to business outcomes (e.g., sales performance, supply chain efficiency, customer experience).
• Collaborate with business and IT teams to identify key metrics and integrate them into dashboards and alerting systems.
• Implement AIOps solutions using industry-leading platforms like OpenAI, AWS Bedrock, Google Gemini, Anthropic, and similar technologies.
• Develop predictive analytics and anomaly detection models to proactively identify and resolve operational issues.
• Integrate observability tools with ITSM platforms and automation workflows. Enable automated root cause analysis and remediation using AI/ML models.
• Provide observability strategies for infrastructure (servers, storage, cloud), applications (microservices, APIs), and networks (LAN/WAN, SD-WAN). Collaborate with DevOps, SRE, and IT operations teams to ensure end-to-end visibility and reliability.
• Establish observability standards, KPIs, and SLAs for performance and availability. Ensure compliance with security and regulatory requirements in monitoring solutions.
• Develop scalable architecture using LLMs, agentic frameworks, and multi-modal AI technologies.
• Build AI-powered analytics platforms for IT operations analysis, anomaly detection, and predictive insights.
• Architect and deploy intelligent chatbots for IT support and self-service capabilities.
• Integrate AI solutions with existing IT operations tools and workflows.
• Implement automated remediation and root cause analysis using AI/ML models.

Qualifications:

• 10-13 years of relevant experience
• Hands-on experience with Grafana, Dynatrace, and other monitoring platforms.
• Practical experience implementing AI-based solutions for anomaly detection, predictive maintenance, and automated remediation. Familiarity with OpenAI, Bedrock, Gemini, Anthropic, or similar AI platforms.
• Strong understanding of infrastructure, application architectures, and networking. Experience with cloud platforms (AWS, Azure, GCP) and container orchestration (Kubernetes).
• Proficiency in Python, Bash, or similar scripting languages for automation and integration.
• Strong experience with LLMs (OpenAI, Anthropic, Gemini, Bedrock) and agentic AI solutions.
• Hands-on experience in designing AI architectures for enterprise IT environments.
• Proficiency in Python or similar languages for AI model integration and automation.

UiPath Developer – Agentic AI & Maestro

About WonderBotz

WonderBotz is a global leader in intelligent automation, delivering innovative RPA and AI solutions that help organizations scale efficiently, reduce costs, and unlock new opportunities. Our team blends technical expertise with business insight to ensure clients achieve measurable success.

Role Overview

We are seeking a UiPath Developer with hands-on experience in Agentic AI and Maestro orchestration. You will design, build, and optimize automation solutions that integrate advanced AI capabilities, ensuring seamless execution across enterprise-scale environments. This role requires strong technical skills, creativity in solution design, and the ability to collaborate with cross-functional teams.

Key Responsibilities

• Develop, configure, and deploy automation workflows using UiPath Studio and Orchestrator.
• Integrate Agentic AI capabilities into RPA solutions to enable intelligent decision-making.
• Utilize Maestro for orchestration, monitoring, and scaling of automation programs.
• Collaborate with business SMEs to gather requirements and translate them into technical designs.
• Build and maintain reusable components, libraries, and frameworks for automation.
• Conduct testing, debugging, and performance tuning of automation solutions.
• Document processes, technical specifications, and best practices.
• Provide support for production deployments and ongoing maintenance.

Qualifications

• 3–5 years of hands-on UiPath development experience (Studio, Orchestrator, Robots).
• Proven expertise with Agentic AI integration in automation workflows.
• Experience with Maestro for orchestration and enterprise automation management.
• Strong understanding of RPA lifecycle (design, development, testing, deployment, support).
• Familiarity with programming languages (VB.Net, C#, Python, SQL) is a plus.
• Knowledge of AI/ML concepts, NLP, and intelligent document processing preferred.
• UiPath certifications (Developer, Advanced RPA Developer) highly desirable.

Desired Characteristics

• Strong problem-solving and analytical skills.
• Excellent communication skills for technical and non-technical stakeholders.
• Ability to work independently and in collaborative team environments.
• Detail-oriented with a focus on quality and scalability.
• Passion for innovation and continuous learning in automation and AI.

Talent Acquisition Manager – AI Infrastructure & Engineering

San Francisco, California

Hybrid Working

We are expanding our global team and launching a new office in San Francisco.

WNTD is looking for an experienced Talent Acquisition Manager to join our Talent Solutions team and support the continued growth of AI infrastructure and accelerated compute platforms across North America.

This role will support one of the most significant AI infrastructure expansion programmes currently underway, focused on building next generation platforms powered by NVIDIA accelerated compute.

You will work closely with senior technical leaders to attract and hire talent across the full infrastructure stack including software engineering, AI platforms, GPU environments and large scale compute infrastructure.

This is a delivery focused role supporting high growth engineering programmes across AI infrastructure and cloud platforms.

The Role

You will lead hiring across multiple engineering disciplines spanning software engineering, AI infrastructure platforms and high performance compute environments.

Working closely with technical leadership and programme stakeholders, you will build pipelines of high quality candidates and manage fast moving hiring plans across several technical workstreams.

Key Responsibilities

• Build and manage talent pipelines across software engineering, AI infrastructure and GPU compute environments

• Proactively source talent across the United States through mapping, referrals and direct outreach

• Screen candidates for technical capability, experience and long term fit

• Partner with engineering leaders to define hiring priorities and role requirements

• Maintain clear tracking of hiring pipelines and delivery progress

• Support wider Talent Solutions activity during peak delivery phases

• Ensure a professional and consistent candidate experience

• Champion fair and inclusive hiring practices

Key Experience

• Proven experience hiring across complex engineering environments

• Strong track record building pipelines across software and infrastructure roles

• Comfortable engaging with technical stakeholders and discussing engineering topics

• Excellent communication and stakeholder management skills

• Strong organisation with the ability to manage multiple roles simultaneously

What We Offer

• Competitive salary and benefits

• Opportunity to support one of the fastest growing AI infrastructure build programmes globally

• Growth within a high performing delivery focused team

• Hybrid working model

• A collaborative culture that values ownership, pace and problem solving

Additional Requirements

• Ability to commute to the San Francisco office

• No visa sponsorship available

• Hybrid working model

A well-funded startup with strong enterprise traction is building a category-defining AI workbench to accelerate enterprise AI adoption.

The platform ingests messy, real workflows, automates them end-to-end, and continuously learns from human decision-making. This is a customer-focused, hands-on engineering role centred on shipping reliable, production-ready AI systems.

As a Customer facing Full stack Engineer, you'll partner with customers, product, and engineering to build and scale AI directly within enterprise workflows.

What You'll Do

• Build and deploy AI-powered features across frontend, backend, and platform

• Implement LLM systems including RAG, embeddings, agents, and document processing

• Rapidly prototype using real customer data and iterate quickly

• Ship user-facing AI with strong guardrails, reliability, and UX

• Optimize for performance, latency, safety, and scale

• Contribute to architecture, testing, and production readiness

• Develop reusable platform components and prompt frameworks

What You Bring

• BS required, Master's preferred

• Experience in a Forward Deployed Engineering role

• Proven track record deploying AI systems into production

• Strong hands-on experience with LLMs and RAG

• Solid software engineering fundamentals

• Comfort in 0 to 1, early-stage environments

• Familiarity with enterprise workflows and unstructured data

Compensation

• Up to $350,000 total comp

• Strong bonus

• Competitive equity

• Hybrid, 3 days onsite in Palo Alto

You'll help transform fragmented enterprise workflows into a continuously improving AI platform, shaping a product already seeing strong demand.

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:

Location: Dallas, Texas, United States

We are looking for a senior business development leader to drive growth in the rapidly expanding AI Data Center construction and infrastructure market. This role is ideal for a strategic professional with strong industry relationships and a proven track record of winning large-scale AI / hyperscale data center projects.

The successful candidate will lead business development initiatives, build strategic partnerships, and secure high-value projects within the AI and hyperscale data center ecosystem.

Key Responsibilities

• Lead business development strategy for AI and hyperscale data center construction projects

• Identify and secure new opportunities with AI companies, hyperscalers, developers, and data center operators

• Build and maintain executive-level relationships with key stakeholders and decision-makers

• Manage the full sales lifecycle from lead generation to contract closure

• Collaborate with internal teams including engineering, construction, and project management

• Track industry trends, emerging technologies, and market opportunities in AI infrastructure

Requirements

• 10+ years of experience in business development, sales, or strategic partnerships

• Strong background in data center development, construction, or mission-critical infrastructure

• Demonstrated success in securing large-scale data center or AI infrastructure projects

• Established network with hyperscalers, AI companies, developers, or colocation providers

• Excellent leadership, negotiation, and relationship management skills

About Wakefern

Wakefern Food Corp. is the largest retailer-owned cooperative in the United States and supports its co-operative members' retail operations, trading under the ShopRite®, Price Rite®, The Fresh Grocer®, Dearborn Markets®, and Gourmet Garage® banners.

Employing an innovative approach to wholesale business services, Wakefern focuses on helping the independent retailer compete in a big business world. Providing the tools entrepreneurs need to stay a step ahead of the competition, Wakefern’s co-operative members benefit from the company’s extensive portfolio of services, including innovative technology, private label development, and best-in-class procurement practices.

The ideal candidate will have a strong background in designing, developing, and implementing complex projects, with focus on automating data processes and driving efficiency within the organization. This role requires a close collaboration with application developers, data engineers, data analysts, data scientists to ensure seamless data integration and automation across various platforms. The Data Integration & AI Engineer is responsible for identifying opportunities to automate repetitive data processes, reduce manual intervention, and improve overall data accessibility.

Essential Functions

• Participate in the development life cycle (requirements definition, project approval, design, development, and implementation) and maintenance of the systems.
• Implement and enforce data quality and governance standards to ensure the accuracy and consistency.
• Provide input for project plans and timelines to align with business objectives.
• Monitor project progress, identify risks, and implement mitigation strategies.
• Work with cross-functional teams and ensure effective communication and collaboration.
• Provide regular updates to the management team.
• Follow the standards and procedures according to Architecture Review Board best practices, revising standards and procedures as requirements change and technological advancements are incorporated into the >tech_ structure.
• Communicates and promotes the code of ethics and business conduct.
• Ensures completion of required company compliance training programs.
• Is trained – either through formal education or through experience – in software / hardware technologies and development methodologies.
• Stays current through personal development and professional and industry organizations.

Responsibilities

• Design, build, and maintain automated data pipelines and ETL processes to ensure scalability, efficiency, and reliability across data operations.
• Develop and implement robust data integration solutions to streamline data flow between diverse systems and databases.
• Continuously optimize data workflows and automation processes to enhance performance, scalability, and maintainability.
• Design and develop end-to-end data solutions utilizing modern technologies, including scripting languages, databases, APIs, and cloud platforms.
• Ensure data solutions and data sources meet quality, security, and compliance standards.
• Monitor and troubleshoot automation workflows, proactively identifying and resolving issues to minimize downtime.
• Provide technical training, documentation, and ongoing support to end users of data automation systems.
• Prepare and maintain comprehensive technical documentation, including solution designs, specifications, and operational procedures.

Qualifications

• A bachelor's degree or higher in computer science, information systems, or a related field.
• Hands-on experience with cloud data platforms (e.g., GCP, Azure, etc.)
• Strong knowledge and skills in data automation technologies, such as Python, SQL, ETL/ELT tools, Kafka, APIs, cloud data pipelines, etc.
• Experience in GCP BigQuery, Dataflow, Pub/Sub, and Cloud storage.
• Experience with workflow orchestration tools such as Cloud Composer or Airflow
• Proficiency in iPaaS (Integration Platform as a Service) platforms, such as Boomi, SAP BTP, etc.
• Develop and manage data integrations for AI agents, connecting them to internal and external APIs, databases, and knowledge sources to expand their capabilities.
• Build and maintain scalable Retrieval-Augmented Generation (RAG) pipelines, including the curation and indexing of knowledge bases in vector databases (e.g., Pinecone, Vertex AI Vector Search).
• Leverage cloud-based AI/ML platforms (e.g., Vertex AI, Azure ML) to build, train, and deploy machine learning models on a scale.
• Establish and enforce data quality and governance standards for AI/ML datasets, ensuring the accuracy, completeness, and integrity of data used for model training and validation.
• Collaborate closely with data scientists and machine learning engineers to understand data requirements and deliver optimized data solutions that support the entire machine learning lifecycle.
• Hands-on experience with IBM DataStage and Alteryx is a plus.
• Strong understanding of database design principles, including normalization, indexing, partitioning, and query optimization.
• Ability to design and maintain efficient, scalable, and well-structured database schemas to support both analytical and transactional workloads,
• Familiarity with BI visualization tools such as MicroStrategy, Power BI, Looker, or similar.
• Familiarity with data modeling tools.
• Familiarity with DevOps practices for data (CI/CD pipelines)
• Proficiency in project management software (e.g., JIRA, Clarizen, etc.)
• Familiarity with DevOps practices for data (CI/CD pipelines)
• Strong knowledge and skills in data management, data quality, and data governance.
• Strong communication, collaboration, and problem-solving skills.
• Ability to work on multiple projects and prioritize tasks effectively.
• Ability to work independently and in a team environment.
• Ability to learn new technologies and tools quickly.
• The ability to handle stressful situations.
• Highly developed business acuity and acumen.
• Strong critical thinking and decision-making skills.

Working Conditions & Physical Demands

This position requires in-person office presence at least 4x a week.

Compensation and Benefits

The salary range for this position is $75,868 - $150,644. Placement in the range depends on several factors, including experience, skills, education, geography, and budget considerations.

Wakefern is proud to offer a comprehensive benefits package designed to support the health, well-being, and professional development of our Associates. Benefits include medical, dental, and vision coverage, life and disability insurance, a 401(k) retirement plan with company match & annual company contribution, paid time off, holidays, and parental leave.

Associates also enjoy access to wellness and family support programs, fitness reimbursement, educational and training opportunities through our corporate university, and a collaborative, team-oriented work environment. Many of these benefits are fully or partially funded by the company, with some subject to eligibility requirements

We're hiring an AI Conversation Designer

Sci-Rec are currently partnering with a fast-growing AI SaaS company transforming behavioral health.

This isn't just about building chatbots. It's about designing AI that navigates some of the most sensitive, high-stakes conversations in healthcare.

You'll be the bridge between human psychology and LLMs,crafting the voice, logic, and flow of AI agents that genuinely help people at their most vulnerable.

What you'll be doing: Designing dialogue flows for complex clinical workflows. Building the behavioral logic that keeps AI empathetic under pressure. Turning interaction data into sharper, more human conversations.

You're the right fit if you: Have 4+ years in conversation design, UX, or HCI with an LLM/agentic AI focus Obsess over the nuance of language Thrive in fast-moving, ambiguous environments Know your way around model constraints, temperature, and prompt logic

Bonus points for a background in linguistics, cognitive science, or psychology.

Early-stage. Meaningful equity. Genuinely important work.