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 disability plans in accordance with the plan documents, which may be amended from time to time. You will be eligible for benefits on the first day of employment with the Company. In addition, you are eligible to participate in the Company 401(k) Plan after 30 days of employment, in accordance with the applicable plan terms. The Company provides for 11 paid holidays and 12 weeks of Parental Leave. We also follow a “free time” PTO policy, allowing you the flexibility to take the time needed for either sick time or vacation.
Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
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