## Job highlights
- 5+ years professional Rust experience with strong ownership, concurrency, and graph algorithm skills; AI/LLM integration and API interop expertise
- Design and implement high-performance Rust algorithms and services; benchmark against Python; build bindings for AI agent frameworks; integrate Rust with LLM systems; develop APIs; collaborate with AI/ML engineers; contribute to CI/CD pipelines

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 up-to-date 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

📌 Rust Developer (Bengaluru)
🏢 EY
📍 Bengaluru