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Fractal Analytics

Enterprise AI solutions for decision making

Lead GenAI Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeSunnyvale, CA, USA

About the Job

Requirements

  • At least 8 years of overall engineering experience, including at least 4 years of hands-on experience building, shipping, scaling, and maintaining production generative AI or large language model systems; prototype, proof-of-concept, or research-only experience is insufficient.
  • Demonstrated experience personally building retrieval-augmented generation pipelines, multi-agent or agentic systems, and large-language-model-powered analytics or decision-support workflows, with concrete quantified outcomes.
  • Deep hands-on expertise with agent orchestration frameworks such as LangGraph, LangChain, LlamaIndex, CrewAI, or OpenAI or Anthropic agent software development kits.
  • Practical experience with modern generative AI 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 with agentic coding harnesses and AI-assisted development tools such as Claude Code, Cursor, or equivalent as part of the build workflow.
  • 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 large language model 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.
  • Ability to operate in fast-moving, ambiguous environments where scope evolves.
  • First-principles thinking and ability to evaluate trade-offs, challenge assumptions, and design modular, defensible systems.
  • Must be based in the United States and in the PST or MST time zone.
  • A bachelor's degree is required.

Responsibilities

  • Design, build, and ship production generative AI systems end to end, remaining hands-on in the codebase.
  • Own architecture across large language model orchestration, retrieval, agentic workflows, evaluation, and the analytics delivery layer.
  • Rapidly prototype against evolving requirements and harden successful approaches into production-ready systems.
  • Set technical direction for a distributed offshore engineering team and own the quality of shipped work.
  • Establish evaluation, observability, and guardrails so system quality is measurable and defensible.

Desired Qualifications

  • A master's degree in computer science, artificial intelligence, machine learning, or a related technical field.
  • Hands-on experience with Model Context Protocol 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 large language model or cloud AI platforms such as AWS Bedrock, Azure OpenAI, Anthropic Claude, or Google Vertex AI.
  • Experience with large language model operations tooling such as LangSmith, MLflow, Weights & Biases, or equivalent.

About the Company

Fractal Analytics

Enterprise AI solutions for decision making

Fractal Analytics provides AI-powered analytics and decision-support solutions for large enterprises, including Fortune 500 companies. Its products combine data science, machine learning, and natural language processing to extract insights, automate tasks, and enable conversations: Crux Intelligence (BI), Senseforth.ai (conversational AI), Eugenie.ai (sustainability), and Asper.ai (revenue growth). The company differentiates itself with a broad, enterprise-focused product portfolio and a global delivery footprint of 4,000+ employees across 16 locations, plus industry analyst recognition and workplace awards. Its goal is to power every human decision in the enterprise by bringing AI, engineering, and design together to help leading companies make better decisions.

Company size
5,001-10,000
Company stage
IPO
Headquarters
New York City, New York
Founded
2000

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