Distinguished Agent Engineer

fastino.ai; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Fastino is building specialized, efficient language models to outperform general models on targeted tasks. As Distinguished Agent Engineer, you will set the technical direction for agent construction on Fastino models, write core code, and raise the bar for the team.

You have shipped agentic systems used by real customers and possess strong opinions on what works. You will design architectures for agentic systems, benchmark performance, and collaborate with research to translate architectures

Qualifications

• 5+ years of software engineering, with 3+ years building with LLMs or ML in production.
• Track record shipping agentic systems used by real users.
• Deep experience across the stack: prompt engineering, tool/API design, vector DBs, Kubernetes, inference serving.
• Strong understanding of model behavior: fine-tuning, evals, latency/cost tradeoffs.
• Experience setting technical direction across teams, not just within one project.
• Clear writing; able to simplify complex systems.
• Bonus: high-concurrency microservices for agent workloads.
• Bonus: familiarity with GLiNER or information extraction architectures.

Responsibilities

• Design and own the architecture for agentic systems built on Fastino's small, fast models.
• Figure out where specialized models beat frontier LLMs inside agent loops, with benchmarks and workloads.
• Build evals, telemetry, and feedback loops to show agent improvement or regression.
• Partner with research to turn new model architectures into agent capabilities and guide future work.
• Make agents fast and reliable at scale: low latency inference and high concurrency serving.
• Drive data and fine-tuning strategy for tasks like tool calling, extraction, and routing.

Skills

LLMs in prod

Agentic systems

System design

Kubernetes

Inference serving

Tool design

Prompt engineering

Tools

Kubernetes

API design

Vector DBs

Job description

Distinguished Agent Engineer

Full-time | San Francisco

About Fastino

• We'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.

• Our open source GLiNER models have been downloaded 50M+ times and are used by teams at NVIDIA, Meta, and Airbnb.

• We've raised $25M (covered in TechCrunch) from Microsoft, Khosla Ventures, Insight Partners, GitHub CEO Thomas Dohmke, Docker CEO Scott Johnston, and others.

The Role

This 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.

What You'll Work On

• Design and own the architecture for agentic systems built on Fastino's small, fast models: planning, tool use, memory, and multi-agent orchestration.

• Figure out where specialized models beat frontier LLMs inside agent loops, and prove it with benchmarks and real customer workloads.

• Build the evals, telemetry, and feedback loops that tell us when agents are getting better (or worse) and why.

• Partner with research to turn new model architectures into agent capabilities, and shape what research works on next.

• Make agents fast and reliable at scale: low latency inference, high concurrency serving, graceful failure handling.

• Drive data and fine-tuning strategy for agent specific tasks like tool calling, extraction, and routing.

What We're Looking For

• 5+ years of software engineering experience, with 3+ years building with LLMs or ML in production.

• A track record of shipping agentic systems that real users rely on, and the scars to prove it.

• Deep experience across the stack: prompt and context engineering, tool and API design, vector DBs, Kubernetes, and inference serving.

• Strong understanding of model behavior: fine-tuning, evals, failure modes, and latency/cost tradeoffs.

• Experience setting technical direction across teams, not just within one project.

• You write clearly and make complicated systems feel simple.

• Bonus: experience building high concurrency microservices for agent workloads.

• Bonus: familiarity with GLiNER or other information extraction architectures.

• Bonus: open source contributions, papers, or talks on agents or LLM systems.