Associate AI Engineer
Fuel Cycle
About the Role
Fuel Cycle empowers leading organizations with agile research solutions that deliver decision-ready insights. Our AI-powered Insights Platform is built for speed, precision, and scale. We help brands make smarter, customer-led decisions. Join a high-growth team where curiosity is valued, ownership is encouraged, and your work drives real-world impact. This is an early-career role. Engineers new to the field are welcome, as are engineers with a year or two of experience who want to go deeper into AI and agentic systems. This role is fully in-office in Los Angeles.
What You’ll Work On
- Design, build, and improve AI agents, deciding how tool-calling loops, model configuration, and multi-step workflows are structured using Strands Agents and AWS Bedrock.
- Build and integrate MCP tools and servers, and learn how tool names and descriptions shape what an LLM does.
- Deploy and run agents on Bedrock AgentCore, working with the platform team and your mentor.
- Build RAG pipelines over pgvector or FAISS, choosing chunking, embedding, and retrieval approaches.
- Design, test, and iterate on prompts; evaluate answer quality, latency, and token cost, and decide on tradeoffs.
- Evaluate models, tools, and approaches, and recommend which to use, with reasoning documented.
- Ship features and bug fixes in FastAPI services (REST and WebSocket APIs backed by PostgreSQL and Redis), deciding on design, implementation, and testing.
- Contribute to background jobs and queue consumers.
- Apply architectural standards, use judgment on design choices, help keep design documents current, and flag where standards should change.
- Submit pull requests, respond to review feedback, and review teammates’ code.
Requirements & Tech Stack
- Solid Python (functions, classes, type hints, error handling, testing basics).
- Data structures and algorithms, with awareness of time and space complexity.
- SQL fundamentals (joins, aggregations, indexes, schema design); PostgreSQL exposure preferred.
- REST and HTTP concepts, and how a web API is structured.
- Git and pull-request workflow.
- Clear communication, comfort asking questions, and a habit of picking up new tools and asking for help.
Preferred
- An agent project built with Strands Agents, LangChain, the OpenAI SDK, or a similar framework.
- Model Context Protocol (MCP): building or using MCP tools and servers.
- AWS Bedrock or Bedrock AgentCore, or AWS basics (S3, SQS).
- RAG: chunking, embeddings, and vector stores.
- Prompt engineering: writing, testing, and iterating on prompts.
- FastAPI or a similar framework (Flask, Django), SQLAlchemy or another ORM, and a willingness to learn async Python.
Qualifications
- Bachelor’s or Master’s in Computer Science or a related field, or equivalent practical experience.
- A track record of learning quickly, shown through coursework, projects, work, open-source contributions, or community involvement.
Compensation
- Starting salary range: $90,000 - $110,000.
- Eligible for variable bonus.
- May include an equity grant or purchase option.