Rust Developer - AI and Systems Engineering

What You’ll Do

• Design and implement performance-critical algorithms and services in Rust (graph algorithms, optimization routines, simulation engines, data pipelines)
• Benchmark and profile Rust implementations against alternatives (e.g., Python) to validate performance gains at scale
• Build bindings/interfaces (FFI, PyO3, gRPC, REST) so Rust-based compute modules can be called from AI agent frameworks and orchestration layers
• Integrate Rust services with LLM-based systems feeding structured outputs into agents built with LangGraph/LangChain or similar frameworks
• Design APIs and data contracts between high-performance Rust backends and AI/agent orchestration layers
• Write clean, memory-safe, well-tested, production-grade Rust (ownership/borrowing discipline, no unsafe unless justified)
• Collaborate with AI/ML engineers to identify which workloads should live in Rust vs. Python vs. an LLM call, based on latency, cost, and correctness needs
• Contribute to CI/CD pipelines using modern DevOps tools for building, testing, and deploying Rust services in containerized environments

Required Skills

• Rust: 5+ years professional experience; strong grasp of ownership, lifetimes, traits, concurrency (async/tokio or similar)
• Algorithms & data structures: comfortable implementing and optimizing graph algorithms (e.g., Dijkstra, A*), simulations, or numerical routines
• Python: working proficiency, enough to compare/benchmark against Rust implementations and integrate with AI/ML tooling
• AI/LLM integration experience: has built or integrated with agent frameworks (LangGraph, LangChain, or custom orchestration), or has hands-on experience calling LLM APIs (Claude, OpenAI, etc.) via SSE/streaming or batch
• APIs & interop: experience exposing Rust functionality via FFI, PyO3, gRPC, or REST/HTTP services
• Containerization: Docker experience; comfortable working in CI/CD pipelines

Nice to Have

• Experience with graph databases (Neo4j) or spatial/routing optimization problems
• Background in engineering, industrial, or infrastructure domains (EPC, energy, manufacturing)
• Background in engineering, industrial, infrastructure, manufacturing, logistics, or other optimization-heavy domains
• Exposure to cloud container orchestration platforms such as Kubernetes or managed cloud container services
• Experience with Supabase Edge Functions or similar serverless compute for lightweight AI-adjacent services