Boson AI

Software Engineer - Platform & Application at Boson AI (Santa Clara, CA)

Boson AI· Santa Clara, CA· $150k–$270k·

Role details

Salary
$150k–$270k
Work type
Onsite
Employment
Full-Time

Job description

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.

Why work at Boson AI

  • Culture: Described as “a diverse group of researchers, engineers, and industry specialists united by a passion for innovation.” Emphasis on building scalable AI that serves millions.
  • Work policy: Most roles are on-site at Santa Clara HQ or Toronto office. A Site Reliability Engineer role was listed as remote (Toronto). Likely hybrid/on-site for core engineering.
  • Engineering environment: Deep technical stack (PyTorch, TensorFlow, Kubernetes, NVIDIA, Supermicro, etc.). Opportunity to work on frontier AI models and real-time systems.
  • Growth stage: Small team (~32 people) with strong research roots; employees have previously worked at AWS, Google, Robinhood, and alumni go to OpenAI, Anthropic, xAI – indicating high-caliber talent and career mobility.
  • Hiring process: Uses AI tools to assist with resume review and analysis, but final decisions made by humans.

Application questions