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Salary
$150k – $270k per year
Location
In office (Santa Clara)
Employment
Full-Time
Overview
Company
Impact
Profile match

About Boson AI: At Boson AI, we are not just building AI solutions; we are pioneering the future of enterprise AI. Driven by a passion for cutting-edge AI research, particularly in the transformative areas of large language models and agentic systems, our mission is to tackle the most complex real-world problems for businesses and unlock significant value. We are a dynamic and collaborative team of researchers and engineers who thrive on pushing the boundaries of what's possible, dedicated to delivering high-quality, reliable products that seamlessly integrate into the fabric of enterprise workflows and set new industry standards.

About the Role: Help build and operate the core platform behind Boson's model APIs and agentic products. You'll work alongside senior engineers on the infrastructure that every Boson agent runs on - API serving, state management, data pipelines, context retrieval, and execution runtime - shipping real features while growing into deeper ownership over time. This is a role for someone early in their career who wants to learn distributed systems by building them, with strong mentorship and meaningful production responsibility from day one.

Responsibilities

  • Contribute to the core platform infrastructure: the API serving layer, state management, policy enforcement, and execution runtime for agentic workflows - starting with well-scoped components and taking on broader ownership as you grow.
  • Help build and maintain distributed services that back our model API products, including request routing, rate limiting, and multi-tenant isolation, under the guidance of senior engineers.
  • Build and maintain pieces of our data pipelines (ETL/ELT) for API logs, usage analytics, and billing, with a focus on data correctness and freshness.
  • Develop and improve internal SDKs and libraries - writing clean, well-tested code with clear contracts that product teams can rely on.
  • Support our context and memory systems for conversational workloads: retrieval, caching, and integration with vector stores and retrieval pipelines.
  • Add observability across the platform - structured logging, tracing, and metrics - and help investigate and resolve reliability issues.
  • Collaborate with ML and product teams to integrate model serving, voice runtime, and tooling infrastructure, learning how the full stack fits together.

Qualifications

  • 0-2 years of professional software engineering experience (internships, co-ops, and strong personal or open-source projects count), or a recent CS degree with equivalent hands-on work.
  • Solid programming fundamentals and a genuine interest in backend and distributed systems - you understand concepts like concurrency and fault tolerance and are eager to apply them in production.
  • Some exposure to building backend services, APIs, or data processing - through work, coursework, or projects.
  • Proficiency in at least one language such as Python, Go, Java, Rust, or C++, and a willingness to pick up new ones.
  • Familiarity with the basics of cloud infrastructure (AWS/GCP), containers (Docker/K8s), version control, and CI/CD - or clear enthusiasm to learn them quickly.
  • Curiosity, strong communication, and a collaborative mindset - you ask good questions, welcome feedback, and want to grow.

Bonus points

  • Coursework, projects, or internship experience touching LLM serving, retrieval, or agentic systems.
  • Exposure to data pipeline tools (Kafka/Kinesis, Spark/Flink, Airflow) or agent frameworks.
  • Experience with real-time media (audio/video streaming) or any latency-sensitive system.
  • A track record of shipping something end-to-end - a side project, a hackathon build, or an open-source contribution you're proud of.
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