{"id":2847291,"url":"https://alion.io/job/fastino-distinguished-agent-engineer","title":"Distinguished Agent Engineer","company":{"id":44225,"name":"Fastino","domain":"fastino.ai","url":"https://alion.io/company/fastino","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":181000,"max_usd":371000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":730},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Context Engineering","optional":false},{"name":"Docker","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Function Calling","optional":false},{"name":"GitHub","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Tool Use","optional":false}],"status":"live","first_seen_at":"2026-10-19T10:17:05Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-20T19:37:27Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Distinguished Agent Engineer\nFull-time | San Francisco or Remote\nAbout Fastino\nWe're building specialized, efficient language models that beat big general models on the tasks that matter. Our team includes alumni from Google Research, Apple, Stanford, and Cambridge.\n\nOur open source GLiNER models have been downloaded 50M+ times and are used by teams at NVIDIA, Meta, and Airbnb.\n\nWe've raised $25M (covered in TechCrunch) from Microsoft, Khosla Ventures, Insight Partners, GitHub CEO Thomas Dohmke, Docker CEO Scott Johnston, and others.\n\nThe Role\nThis is one of our most senior IC engineering role. You'll set the technical direction for how agents get built on Fastino models, write a lot of the core code yourself, and raise the bar for everyone around you. You've built agentic systems that real users depend on, and you have strong opinions about what works.\nWhat You'll Work On\nDesign and own the architecture for agentic systems built on Fastino's small, fast models: planning, tool use, memory, and multi-agent orchestration.\n\nFigure out where specialized models beat frontier LLMs inside agent loops, and prove it with benchmarks and real customer workloads.\n\nBuild the evals, telemetry, and feedback loops that tell us when agents are getting better (or worse) and why.\n\nPartner with research to turn new model architectures into agent capabilities, and shape what research works on next.\n\nMake agents fast and reliable at scale: low latency inference, high concurrency serving, graceful failure handling.\n\nDrive data and fine-tuning strategy for agent specific tasks like tool calling, extraction, and routing.\n\nWhat We're Looking For\n5+ years of software engineering experience, with 3+ years building with LLMs or ML in production.\n\nA track record of shipping agentic systems that real users rely on, and the scars to prove it.\n\nDeep experience across the stack: prompt and context engineering, tool and API design, vector DBs, Kubernetes, and inference serving.\n\nStrong understanding of model behavior: fine-tuning, evals, failure modes, and latency/cost tradeoffs.\n\nExperience setting technical direction across teams, not just within one project.\n\nYou write clearly and make complicated systems feel simple.\n\nBonus: experience building high concurrency microservices for agent workloads.\n\nBonus: familiarity with GLiNER or other information extraction architectures.\n\nBonus: open source contributions, papers, or talks on agents or LLM 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