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SiftstackSiftstackMarina Del Rey, CA

Senior Software Engineer, Backend

Build and operate dependable agentic AI systems that analyze large-scale hardware telemetry for engineering teams. Own product areas end-to-end, from customer conversations to designing tools, APIs, distributed execution on Kubernetes, evaluation frameworks, and integrating frontier models. Requires 8+ years software engineering experience with backend services and distributed systems.

200k – 250k/yr
Hybrid8+ YOEML Engineering

About the role

Responsibilities

  • Talk directly to customers and partner with product to turn real review workflows into agent capabilities: generating dashboards, writing analysis scripts, and surfacing insights buried in their telemetry.
  • Design, ship, and operate agentic systems that reason over large-scale time-series data and hardware domain context.
  • Build everything around the model that makes agents dependable: tool interfaces, sandboxed execution for agent-generated code, context and memory management, custom compaction algorithms, opinionated skills, and guardrails.
  • Build the distributed systems that let long-running agent work stream in real time, survive disconnects, and resume across restarts.
  • Design job-based execution systems that schedule, scale, and tear down agent workloads on Kubernetes, both in the cloud and on-prem.
  • Develop and maintain Sift’s MCP server, the tool surface that lets both our agents and our customers’ AI tools query telemetry directly.
  • Design and implement the APIs that power our agentic capabilities.
  • Build evaluation suites that measure whether agents actually help engineers, and instrument quality, latency, cost, and failure modes in production.
  • Integrate and assess frontier models across providers.

Requirements

  • 8+ years of professional software engineering experience.
  • Get excited about owning a product area: talking to customers, deciding what to build, and shipping it.
  • Have built APIs (REST, gRPC, etc.) and complex backend services with technologies like Go, Python, Rust, or similar.
  • Have a working knowledge of distributed systems fundamentals.
  • Are curious about new AI products: you try new agents, models, and features as they ship, and have opinions about what makes them good.

Nice-to-Haves

  • Shipped products to users at scale: large data volumes, significant active user counts, or deep technical complexity.
  • Shipped LLM-powered features.
  • Built agentic systems: multi-step tool use, planning loops, context management, and evals.
  • Designed tool ecosystems for agents, including MCP.
  • Worked with sandboxed or isolated execution of generated code.
  • Operated services in production (Kubernetes, observability, incident response).
  • Worked with streaming or time-series data systems (Kafka, Flink, TimescaleDB).
  • A personal ecosystem of AI dev tooling: custom agents, skills, scripts, or workflows built to ship faster.
  • A background in time-series data, scientific computing, or hardware test and telemetry.
  • Built internal agentic tooling that accelerates an engineering org.

Compensation

  • Salary range: $170,000 - $220,000 per year. Plus equity and benefits.

Skills

GoPythonRustKubernetesgRPCPostgresAWSKafkaFlinktimescaledbLLMsDistributed SystemsAPIstime-series data

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