Exp- 5 yrs
Overview
We’re looking for a Rust Developer who enjoys building high-performance systems while working with modern AI technologies. This role combines low-level systems engineering with AI application development, giving you the opportunity to create fast, reliable Rust services that integrate seamlessly with LLM-powered applications and agent workflows.
You’ll help design systems where computationally intensive logic runs efficiently in Rust while AI agents handle reasoning, orchestration, and automation.
Key Responsibilities
High-Performance Rust Development
Develop efficient, production-ready services and algorithms using Rust.
Build and optimize graph algorithms, simulation engines, optimization routines, and large-scale data processing pipelines.
Profile, benchmark, and improve Rust implementations, comparing performance with alternatives such as Python.
AI & Agent Integration
Connect Rust services with AI-powered applications and agent frameworks.
Enable Rust modules to communicate with orchestration layers using interfaces such as PyO3, FFI, gRPC, or REST APIs.
Deliver structured outputs that integrate smoothly into LangGraph, LangChain, or similar agent ecosystems.
Backend Architecture
Define clear APIs and data contracts between Rust services and AI orchestration platforms.
Ensure services are scalable, maintainable, and optimized for production workloads.
Write robust, memory-safe Rust code while following ownership and borrowing best practices. Use unsafe only when clearly justified.
Collaboration & Deployment
Work closely with AI/ML engineers to determine whether workloads should be executed in Rust, Python, or through LLM inference based on performance, accuracy, latency, and cost.
Support CI/CD pipelines and containerized deployments using modern DevOps practices.
Required Qualifications
Rust
5 years of professional Rust development experience.
Strong understanding of ownership, lifetimes, traits, concurrency, async programming, and Tokio (or equivalent).
Algorithms & Performance
Experience implementing and optimizing algorithms such as graph traversal, pathfinding (Dijkstra, A*), simulations, or numerical computation.
Comfortable analyzing runtime performance and benchmarking implementations.
Python
Practical Python experience for benchmarking, interoperability, and AI/ML integration.
AI & LLM Experience
Hands-on experience integrating LLM APIs (OpenAI, Claude, or similar).
Familiarity with AI agent frameworks such as LangGraph, LangChain, or custom orchestration platforms.
Experience working with streaming (SSE) or batch inference workflows.
APIs & Interoperability
Experience exposing Rust functionality through:
FFI
PyO3
gRPC
RESTful APIs
DevOps
Experience using Docker.
Comfortable working with automated build, testing, and deployment pipelines.
Preferred Experience
Candidates with any of the following will stand out:
Graph databases such as Neo4j.
Routing, spatial optimization, or graph-based computation.
Engineering, manufacturing, infrastructure, logistics, energy, EPC, or other optimization-intensive industries.
Kubernetes or managed cloud container platforms.
Supabase Edge Functions or comparable serverless technologies for lightweight AI services.
Why This Role?
Most Rust positions focus entirely on systems programming, while many AI engineering roles concentrate only on prompts and orchestration.
This position brings both worlds together.
You’ll build deterministic, high-performance Rust components that power real-world AI applications while ensuring those systems integrate cleanly with modern LLMs, agent frameworks, and production infrastructure. Your work will directly influence system speed, reliability, scalability, and overall AI performance.