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-secure, 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 contemporary DevOps tools for building, testing, and deploying Rust services in containerized environments

Required Skills
Rust: 5+ years professional experience; solid 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 Ai And Systems Engineering Bengaluru
🏢 EY
📍 Bengaluru