Backend Software Engineer (Agentic AI)

Join Sift, a company revolutionizing the way hardware engineers interact with telemetry data. As a Backend Software Engineer, you will have real product ownership and autonomy, working directly with customers to understand their needs and drive product development. You will design and build agentic systems that reason over large-scale time-series data and hardware domain context, and develop the infrastructure that supports these systems. This is a product engineering role, not a research role, and you will have the opportunity to help evolve and scale our platform.

• Conception, design, and implementation of agentic systems that reason over large-scale time-series data and hardware domain context.
• Collaboration with customers and product teams to turn real review workflows into agent capabilities, including generating dashboards and writing analysis scripts.
• Development and maintenance of Sift’s MCP server, the tool surface that lets both our agents and our customers’ AI tools query telemetry directly.
• Get excited about owning a product area: talking to customers, deciding what to build, and shipping it
• Have a working knowledge of distributed systems fundamentals
• Have 3+ years of professional software engineering experience
• Have built APIs (REST, gRPC, etc.) and complex 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
• If this role excites you, apply even if you don’t check every box
• 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
• Worked with streaming or time-series data systems (Kafka, Flink, TimescaleDB)
• A background in time-series data, scientific computing, or hardware test and telemetry
• Built internal agentic tooling that accelerates an engineering org