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Fractal AnalyticsVerified from Fractal Analytics' careers page · Workday

Lead GenAI Engineer

  • California, USA
  • On-site
  • Posted Sep 9, 2026

Visa sponsorship: the posting says the employer will not sponsor a visa for this role.

Fractal Analytics had H-1B petitions approved for 69 workers in fiscal year 2026 (USCIS). That is history, not a promise for this role. See the record

At a glance

Lead GenAI Engineer at Fractal Analytics, an on-site role based in California, USA. Posted on 9 September 2026, read from Fractal Analytics' own careers page (Workday), which RealAnalystJobs re-checks daily and removes the role when it closes. The posting says the employer will not sponsor a visa for this role. Fractal Analytics has approved H-1B petitions on USCIS record (employer-wide, not a promise for this role).

Similar roles on RealAnalystJobs, as of 15 November 2026

About this role

It's fun to work in a company where people truly BELIEVE in what they are doing! We're committed to bringing passion and customer focus to the business. Lead GenAI Engineer Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner. Please visit Fractal | Intelligence for Imagination for more information about Fractal Location: Bay Area, California (Sunnyvale preferred) Note: This position is not eligible for Immigration Sponsorship at this time. Role Overview: You will be the hands-on technical lead for a GenAI product at the intersection of large language models and enterprise analytics. This is a builder's role. You will personally architect and ship production systems, own delivery quality, and set technical direction for a distributed engineering team. This is not an advisory or architecture-only position. Key Responsibilities Hands-on GenAI Engineering & Delivery • Design, build, and ship production GenAI systems end to end. Remain hands-on in the codebase rather than directing from a distance. • Own the architecture across LLM orchestration, retrieval, agentic workflows, evaluation, and the analytics delivery layer. • Rapidly prototype against evolving requirements and harden successful approaches into production-ready systems. Technical Leadership & Quality • Set technical direction for a distributed offshore engineering team and own the quality of what ships. • Establish evaluation, observability, and guardrails so system quality is measurable and defensible. Required Experience Production GenAI & Agentic Systems • 8+ years of overall engineering experience, including 4+ years of hands-on experience building, shipping, scaling, and maintaining production GenAI or LLM systems. Experience limited to prototypes, proofs of concept, or research is not sufficient. • Demonstrated record of personally building RAG pipelines, multi-agent or agentic systems, and LLM-powered analytics or decision-support workflows, with concrete and quantified outcomes. • Deep hands-on expertise with agent orchestration frameworks such as LangGraph, LangChain, LlamaIndex, CrewAI, or the OpenAI or Anthropic agent SDKs. • Practical experience with modern GenAI patterns, including tool or function calling, structured outputs, hybrid and agentic retrieval, context engineering, prompt and evaluation optimization, and multi-agent coordination. • Hands-on experience using agentic coding harnesses and AI-assisted development tools such as Claude Code, Cursor, or equivalent as part of the build workflow. Backend Engineering, Evaluation & Analytics • Strong Python skills and solid backend engineering fundamentals, including REST and streaming API design, asynchronous patterns, and containerized deployment with Docker and Kubernetes. • Production experience with LLM evaluation and observability, including offline and online evaluations, tracing, hallucination measurement, and quality measurement using RAGAS, LangSmith, or equivalent tools. • Sufficient fluency in data science, machine learning, and business intelligence to reason about analytical accuracy, data quality, and output reliability. Leadership, Education & Location • Proven ability to operate in fast-moving, ambiguous environments where scope evolves. • Strong first-principles thinking, with the ability to evaluate trade-offs, challenge assumptions, and design modular and defensible systems. • US-based; PST or MST timezone required. Sunnyvale or the Bay Area is strongly preferred. • Bachelor's degree required. Master's degree in computer science, artificial intelligence, machine learning, or a related technical field preferred. Preferred Experience • Hands-on experience with Model Context Protocol (MCP) or agent-native enterprise platforms. • Experience building and orchestrating custom agents, tools, and harnesses beyond off-the-shelf usage. • Background in analytics, business intelligence, or data products where AI intersects with enterprise reporting and decision-making. • Experience with Text-to-SQL or natural-language-to-analytics systems. • Consulting or client-embedded delivery experience in matrixed organizations with distributed teams. • Certifications across LLM or cloud AI platforms such as AWS Bedrock, Azure OpenAI, Anthropic Claude, or Google Vertex AI. • Experience with LLMOps tooling such as LangSmith, MLflow, Weights & Biases, or equivalent. Pay: The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions, including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.  The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled.  At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case.  A reasonable estimate of the current range is: Up to $185,000 . In addition, you may be eligible for a discretionary bonus for the current performance period. Benefits: As a full-time employee of the company or as an hourly employee working more than 30 hours per week, you will be eligible to participate in the health, dental, vision, life insurance, and disabili

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