Senior Software Engineer (Backend, Agentic AI)

Join Sift, a leading AI company, as a Senior Software Engineer (Backend, Agentic AI). In this role, 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 and maintain Sift's MCP server. This is a product engineering role, not a research role, and you will be working with a wide range of technologies. Benefits include free lunch, unlimited PTO, and top-tier health insurance.

• Concevoir, expédier et exploiter des systèmes agentiques qui raisonnent sur des données temporelles à grande échelle et le contexte du domaine matériel.
• Développer et maintenir le serveur MCP de Sift, la surface d'outil qui permet à la fois à nos agents et aux outils d'IA de nos clients d'interroger directement la télémétrie.
• Construire des systèmes distribués qui permettent à un travail d'agent de longue durée de s'écouler en temps réel, de survivre aux déconnexions et de reprendre après des redémarrages.
• If this role excites you, apply even if you don’t check every box
• Have 8+ years of professional software engineering experience
• Are curious about new AI products: you try new agents, models, and features as they ship, and have opinions about what makes them good
• Have built APIs (REST, gRPC, etc.) and complex backend services with technologies like Go, Python, Rust, or similar
• 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
• Shipped LLM-powered features
• Shipped products to users at scale: large data volumes, significant active user counts, or deep technical complexity
• Designed tool ecosystems for agents, including MCP
• Built agentic systems: multi-step tool use, planning loops, context management, and evals
• Operated services in production (Kubernetes, observability, incident response)
• Worked with sandboxed or isolated execution of generated code
• 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