{"id":3186858,"url":"https://alion.io/job/fuel-cycle-associate-ai-engineer","title":"Associate AI Engineer (Onsite in Los Angeles)","company":{"id":8205,"name":"Fuel Cycle","domain":"fuelcycle.com","url":"https://alion.io/company/fuel-cycle","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":76,"open_postings":15,"ghost_share":0.4,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":47,"computed_at":"2026-10-28T05:59:10Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Los Angeles, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":90000,"max":110000,"currency":"USD","period":"year","gross":null,"usd_annual":110000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Bedrock AgentCore","optional":false},{"name":"AWS Strands Agents","optional":false},{"name":"Django","optional":false},{"name":"Embeddings","optional":false},{"name":"FAISS","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"Git","optional":false},{"name":"LangChain","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenAI SDK","optional":false},{"name":"pgvector","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Redis","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"SQLAlchemy","optional":false},{"name":"WebSockets","optional":false}],"status":"live","first_seen_at":"2026-10-23T21:58:02Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-28T09:14:10Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":4},"description":"About Fuel Cycle:\nFuel Cycle empowers leading organizations with agile research solutions that deliver decision-ready insights - fast, flexible, and fully integrated. As a market research disruptor, our AI-powered Insights Platform is built for speed, precision, and scale. With cutting-edge tools and seamless audience connectivity, we help brands ditch the guesswork and make smarter, customer-led decisions at lightning speed.\nWhy work at Fuel Cycle?\nJoin a high-growth team where curiosity is valued, ownership is encouraged, and your work drives real-world impact. Whether you’re based at our Los Angeles HQ, New York City hub, working remotely across the U.S., or part of our global team in India, you’ll help shape the future of decision intelligence for some of the world’s most iconic brands.\nOverview:\nBuild real AI agents on a production platform, with senior engineers working alongside you. You will work in Python and FastAPI, build tool-calling agents on AWS Bedrock and AgentCore using the Strands Agents framework, and own technical decisions within the problems you take on, with your scope growing as you do. This role is fully in-office in Los Angeles because our mentorship model depends on it: pair programming, in-person code review, and a mentor a few desks away.\nWe hire for fundamentals, curiosity, and initiative. This is an early-career role. Engineers new to the field are welcome, and so are engineers with a year or two of experience who want to go deeper into AI and agentic systems. You do not need to know our stack on day one.\nWhat You’ll Work On:\nDesign, build, and improve AI agents, deciding how tool-calling loops, model configuration, and multi-step workflows are structured using Strands Agents and AWS Bedrock\n\nBuild and integrate MCP tools and servers, and learn how tool names and descriptions shape what an LLM does\n\nDeploy and run agents on Bedrock AgentCore, working with the platform team and your mentor\n\nBuild RAG pipelines over pgvector or FAISS, choosing chunking, embedding, and retrieval approaches based on what the results show\n\nDesign, test, and iterate on prompts; evaluate answer quality, latency, and token cost, and decide which tradeoffs to make; learn how guardrails are applied in production paths\n\nEvaluate models, tools, and approaches, and recommend which to use, with your reasoning documented\n\nShip features and bug fixes in FastAPI services (REST and WebSocket APIs backed by PostgreSQL and Redis), deciding how to design, implement, and test them\n\nContribute to background jobs and queue consumers so agent work runs outside the API request path\n\nApply our architectural standards, use your judgment on design choices within them, help keep design documents current, and flag where the standards should change\n\nSubmit pull requests, respond to review feedback, and review teammates’ code as you grow\n\nWhat You Bring:\nSolid Python from coursework, internships, or work: functions, classes, type hints, error handling, testing basics\n\nData structures and algorithms, with awareness of time and space complexity\n\nSQL fundamentals (joins, aggregations, indexes, schema design); PostgreSQL exposure preferred\n\nREST and HTTP concepts, and how a web API is structured\n\nGit and pull-request workflow\n\nClear communication, comfort asking questions, and a habit of picking up new tools and asking for help when you’re stuck\n\nPreferred:\nAn agent project built with Strands Agents, LangChain, the OpenAI SDK, or a similar framework (coursework, personal, or professional), including how an LLM chooses and calls tools\n\nModel Context Protocol (MCP): building or using MCP tools and servers\n\nAWS Bedrock or Bedrock AgentCore, or AWS basics such as S3 and SQS\n\nRAG: chunking, embeddings, and vector stores\n\nPrompt engineering: writing, testing, and iterating on prompts\n\nFastAPI or a similar framework such as Flask or Django, SQLAlchemy or another ORM, and a willingness to learn async Python\n\nExperience:\nBachelor’s or Master’s in Computer Science or a related field, or equivalent practical experience (bootcamp, self-taught, or on-the-job)\n\nRoughly 0-2 years of software engineering experience; internships, research, and substantial projects count\n\nA track record of learning quickly, shown through coursework, projects, work, open-source contributions, or community involvement\n\nBenefits & Perks:\nFuel Cycle is committed to supporting the well-being, flexibility, and growth of our team. We offer a competitive and inclusive benefits package that includes:\nComprehensive Health Coverage: Medical, dental, and vision insurance plans\n\n401(k) with Company Match: Plan for your future with our retirement savings program\n\nEquity Purchase Option: Participate in Fuel Cycle’s long-term success\n\nFlexible Work Schedule: Empowering you to balance life and work\n\nGenerous Time Off:\n15 vacation days and 7 sick days per year\n\n12 company holidays\n\n4 floating holidays/recharge days to rest or celebrate what matters to you\n\nPaid Parental Leave: Time to bond with your growing family\n\nMonthly Internet & Phone Stipend: Support for remote work setup\n\nWellness & Lifestyle Perks: Access to tools like Rightway (healthcare navigation), Headspace (mental wellness), Peloton (fitness), and more\n\nTeam Connection Perks:\nWeekly community lunches, refreshments, and snacks at our LA & NY headquarters\n\nCompensation Overview:\nThe expected starting salary range for this position is $90,000 - $110,000. This range represents the typical starting compensation offered to candidates hired into this role. Final base salary will be determined based on a variety of factors, including location, work experience, skills, knowledge, education, and certifications.\nIn addition to base salary, this role is eligible for variable bonus, and may include an equity grant or purchase option. These components make up your total compensation package, which will be reviewed in greater detail during your initial recruiter conversation.\nCommitment to Diversity, Equity, and Equal Opportunity:\nAt Fuel Cycle, we embrace the values of diversity, equity, and inclusion and are committed to fostering an inclusive company culture. We believe that everyone, regardless of their background or identity, should have equal access to opportunities for growth and advancement. Our selection processes and career pathways are designed to be fair, transparent, and free from bias. We value the unique perspectives and contributions of each team member, knowing that this diverse range of experiences strengthens our team. Fuel Cycle stands firmly against discrimination based on disability, sex, race, gender identity, sexual orientation, religion, national origin, age, veteran status, or any other protected status under the law.\nFuel Cycle is an equal opportunity employer and fully comply with the Americans with Disabilities Act (ADA). We will provide reasonable accommodations for qualified applicants and employees with disabilities, as needed, to enable them to perform the essential functions of their job and participate in the application and interview process. 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