---
title: 'Software Engineer - Platform & Application at Boson AI'
canonical: 'https://feeny.ai/job/software-engineer-platform-application-boson-ai-santa-clara-zct1esjbfzcn'
type: 'job'
last_seen: '2026-09-11'
---

# Software Engineer - Platform & Application at Boson AI

- **Company:** Boson AI
- **Location:** Santa Clara, CA
- **Compensation:** $150k–$270k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-07-22
- **Last confirmed live:** 2026-09-11
- **Apply:** https://jobs.lever.co/bosonai/2b520a0f-556a-4dc2-a5a7-d8845a921335

## 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.

## About Boson AI

## Company Overview
- **One-liner**: Boson AI builds real-time, audio-native AI models and agentic systems for natural, conversational voice interactions with machines.
- **Entity Type**: Private (funding not disclosed)
- **Headquarters**: Santa Clara, California, United States (also Toronto, Canada office)
- **Founded**: 2023
- **Founders**: Dr. Alex Smola (Co-Founder & CEO/CSO), Dr. Mu Li (Co-Founder & CEO/CTO), Yi Zhu (Co-Founder, departed May 2026), Yizhi Liu (Co-Founder)

## Core Business
- **Primary industries**: Conversational AI, Voice AI, Multimodal AI, Enterprise AI infrastructure
- **Target customers**: B2B – enterprises deploying voice agents, real-time customer service, and AI-powered communication workflows
- **Mission**: “Make communication with machines as easy, natural and fun as talking to a human.”

## Products & Services
- **Higgs Realtime**: An end-to-end, audio-native real-time speech-to-speech model for enterprise voice agents. Supports interruptions, code-switching (100+ languages), ~700ms speech-in to speech-out latency, and API compatibility with OpenAI Realtime (change three lines of code). Pricing: $0.0023/min audio in, $0.014/min audio out. [LinkedIn post](https://linkedin.com/company/boson-ai)
- **Higgs Avatar v1**: Real-time conversational avatar foundation model that generates 480p video at 16 FPS from a single image and streaming audio. Designed for real-time digital presence in voice agents. Private preview announced May 2026. [LinkedIn post](https://linkedin.com/company/boson-ai)
- **Agent Platform (Agent OS)**: An internal platform for building, deploying, and orchestrating AI agents (referenced in job postings as “Member of Technical Staff - Agent Platform”).

## Market Standing
- **Valuation**: Not publicly available
- **Key Metric**: Total funding not disclosed; headcount of 32 employees (as of mid-2026)
- **Notable Investors/Partners**: Not publicly listed. Talent sources include Amazon Web Services (AWS), Google, University of Toronto, Vector Institute, indicating strong ties to top AI research and engineering communities.
- **Growth Signals**: Launch of Higgs Realtime (August 2026) and Higgs Avatar v1 (May 2026); active hiring for senior engineering and ML roles; 10,000+ LinkedIn followers with +2.5% monthly growth; technical team comprises 68% of workforce.

## Competitive Advantages
- **Full-stack AI ownership**: Builds own foundation models (audio, avatar, agent orchestration) rather than stitching external components, enabling deep co-design for low latency and natural interaction.
- **Real-time expertise**: Achieves ~700ms speech-in to speech-out and ~125ms barge-in yield, with top benchmarks in tool-calling and interruption recovery.
- **Cost efficiency**: Higgs Realtime pricing ($0.0023/min audio in) is significantly lower than many competitors, targeting enterprise-scale deployment.
- **Research pedigree**: Founders have “almost a century of expertise in AI” (Alex Smola and Mu Li are well-known ML researchers; Smola co-authored seminal work on kernel methods and scalable ML).

## Strategic Focus
- **Real-time conversational AI for enterprise**: Prioritizing production-ready voice agents that can handle interruptions, code-switching, and emotional alignment.
- **Multimodal expansion**: Adding visual presence (avatars) to voice agents to make interactions more natural and human-compatible.
- **Enterprise deployment**: Offering self-hosting options and private previews for large-scale customers.
- **Building the full agentic pipeline**: From data and modeling to training, tuning, and serving – all in-house.

## Why Work Here
- **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.

## Sources
1. [boson.ai/about](https://www.boson.ai/about)
2. [boson.ai/about/team](https://www.boson.ai/about/team)
3. [linkedin.com/company/boson-ai](https://linkedin.com/company/boson-ai)
4. [jobs.lever.co/bosonai](https://jobs.lever.co/bosonai)

## Other roles at Boson AI

- [Datacenter Technician](https://feeny.ai/job/datacenter-technician-boson-ai-barrie-11tetdz9z3vr) — Barrie, Canada
- [Site Reliability Engineer](https://feeny.ai/job/site-reliability-engineer-boson-ai-toronto-69xyfzggnjaj) — Toronto, Canada
- [Senior Software Engineer - Systems](https://feeny.ai/job/senior-software-engineer-systems-boson-ai-santa-clara-94h0qsa26h84) — Santa Clara, CA
- [Frontend Engineer](https://feeny.ai/job/frontend-engineer-boson-ai-santa-clara-nbsv99agxh8b) — Santa Clara, CA
- [Machine Learning Engineer - Enterprise](https://feeny.ai/job/machine-learning-engineer-enterprise-boson-ai-toronto-cm87w800xvcq) — Toronto, Canada
- [Member of Technical Staff - Agent Platform (Agent OS)](https://feeny.ai/job/member-of-technical-staff-agent-platform-agent-os-boson-ai-santa-clara-95vzvadf5n6c) — Santa Clara, CA