Backend MCP Engineer
Department: Engineering
Location: San Francisco
Compensation: $120K – $180K
Employment Type: FullTime
LiteLLM is the world’s most popular AI Gateway used by the largest companies (Adobe, Netflix, NASA, etc.) in the world to give their developers access to LLMs and adjacent services (MCP’s, Vector Stores, etc.).
Why do companies use LiteLLM enterprise
Companies use LiteLLM Enterprise once they put LiteLLM into production and need enterprise features like Prometheus metrics (production monitoring) and need to give LLM access to a large number of people with SSO (secure sign on) or JWT (JSON Web Tokens).
What you will be working on
Skills: Python, MCP, AI infrastructure, FastAPI
As the Backend MCP Engineer, you'll be responsible for implementing MCP server support, building tool orchestration layers, designing protocol for external tool integration, enabling function calling across multiple LLM providers, and creating SDK for MCP server discovery and connection. You'll work directly with the CEO and CTO on critical projects including:
Adding MCP protocol support to LiteLLM gateway
Building unified tool calling interface across providers
Implementing session management for stateful agents
Creating examples/docs for MCP + LiteLLM integration
What is our tech stack
Core: Python, FastAPI, MCP, Redis, Postgres.
LLM Integration: OpenAI SDK, Anthropic SDK, AWS Bedrock, Vertex AI
Protocol Layer: JSON-RPC, WebSockets, Server-Sent Events (SSE)
Agent Tooling: Model Context Protocol (MCP), function calling, tool schemas
Infrastructure: Docker, Kubernetes, Prometheus, GitHub Actions
You'll work with:
Multiple LLM provider APIs (Anthropic, OpenAI, Google, AWS)
MCP protocol implementation (client + server)
High-throughput async systems (10K+ req/sec)
Open source community (34K+ GitHub stars)
What’s so exciting about this role?
LiteLLM is at the intersection of 3 critical AI infrastructure layers:
1. LLM Gateway - Call any LLM with one API (our core strength)
2. MCP Gateway - Give any LLM access to any tool (emerging need)
3. Agent Gateway - Enable agents to communicate with other agents/llm’s/tools
You'll help us become the unified infrastructure layer that connects:
Applications ↔ LiteLLM ↔ LLM Providers (OpenAI, Anthropic, Bedrock)
LLMs ↔ LiteLLM ↔ MCP Servers (databases, APIs, internal tools)
Agents ↔ LiteLLM ↔ MCP Servers (databases, APIs, internal tools) + LLMs
This means working on cutting-edge problems like:
How do we route tool calls across providers with different specs?
How do we make MCP servers work seamlessly with any LLM?
How do we build the "Stripe of AI infrastructure"? If you're excited about building the foundational layer that every AI application will use, this is for you.
Who we are looking for
1-2 years of backend/full-stack experience with production systems
Passion for open source and user engagement
Experience working with the OpenAI api (understand the difference between /chat/completions and /responses, and can speak to API-specific nuances)
Strong work ethic and ability to thrive in small teams
Eagerness to talk to users and help solve real problems
About the interview
Our interview process is:
Intro call - 30 min
Behavioral discussion about your working style, expectations, and the company’s direction.
Hackerrank - 1 hr
A hackerrank covering basic python questions
Virtual Onsite - 3 hrs
Virtual onsite with founders, which involves solving an issue on LiteLLM’s github together, a presentation of a technical project and a system design question
About LiteLLM
LiteLLM (https://github.com/BerriAI/litellm) is a Python SDK, Proxy Server (LLM Gateway) to call 100+ LLM APIs in OpenAI format - [Bedrock, Azure, OpenAI, VertexAI, Cohere] and is used by companies like Rocket Money, Adobe, Twilio, and Siemens.
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