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Software Engineer - Platform

Job in Santa Clara, Santa Clara County, California, 95053, USA
Listing for: Boson AI
Full Time position
Listed on 2026-07-26
Job specializations:
  • Software Development
    Backend Developer, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 90000 - 130000 USD Yearly USD 90000.00 130000.00 YEAR
Job Description & How to Apply Below
Position: Software Engineer - Platform & Application

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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