Senior Software Engineer - Systems
Boson AI · Santa Clara HQ
$150,000–$400,000
Jul 7, 2026
Santa Clara HQ
Jul 21, 2026
What this job asks for AI summary
A backend platform engineering role focused on building and maintaining the infrastructure that underpins AI model APIs and agentic products. Core responsibilities span API serving, distributed systems, data pipelines for logs and billing, internal SDKs, and observability. Suited to engineers with production experience owning shared backend services, strong distributed systems fundamentals, and comfort across cloud infrastructure and data pipeline tooling.
Mid level · 3+ years · National · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $138,970 (middle half $107,524–$175,762).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (7)
No work location or city is mentioned in the posting; CBSA and state are left blank. The role may be remote or at an unstated office.
The title is simply an implied platform/backend engineer role with no seniority modifier — advertised seniority is Unspecified. The 3+ years requirement and scope (owning services depended on by other teams) map to a Mid-level band; the responsibilities are substantial but not org-wide in the Staff/Principal sense.
The systems-language requirement lists Go, Rust, Java, C++, and Python as explicit alternatives for the same gate; Go is used as the primary name with the others captured as alternatives.
Kafka/Kinesis and Spark/Flink are each listed as interchangeable pairs for the same data-pipeline requirement; emitted as single skills with alternatives accordingly.
Airflow appears alongside Kafka/Kinesis and Spark/Flink under the same pipeline requirement ('or similar'); it is retained as a separate named tool rather than folded in, since it serves a distinct orchestration function.
LLM serving, agentic orchestration (ReAct, planner-executor), RAG pipelines, MCP/A2A protocols, LangChain/LlamaIndex, and real-time media systems all appear under the 'Bonus point' section and are marked preferred.
No compensation figures are provided in the posting.
Read the full posting
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