Senior Software Engineer, Full Stack

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.
• Develop and maintain Sift’s MCP server, the tool surface that lets both our agents and our customers’ AI tools query telemetry directly.
• Work across the whole stack.
• Build the frontend surfaces where Sift Agents live, and make them feel great.
• Design and implement the APIs that power our agentic capabilities.
• Run agents reliably at scale, both in the cloud and on-prem.
• 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 frontend web applications with technologies like React, NextJS, or similar.
• Have built APIs (REST, gRPC, etc.) or backend services with technologies like Go, Python, Rust, or similar.
• 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).
• 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.

Technologies

• Web frontend & backend: ECharts, Go, gRPC, PostgreSQL, Protobuf, Radix, React, Redux, and TypeScript.
• Data: Arrow, DataFusion, Flink, Parquet, and Rust.
• Infrastructure: Argo CD, AWS, Docker, GitHub Actions, Grafana, Kubernetes, Kustomize, Linux, Prometheus, and Terragrunt.

Compensation

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