Senior ML Performance Engineer - AI Infra for Enterprise

Atlassian; Mountain View (CA); On-site; USD 180,000 - 235,000; Full time

Job summary

At Atlassian, join the Agentic AI Integrations team to design and build MCP servers, tools, and agent-facing APIs. You will craft scalable web experiences in React/TypeScript, integrate GraphQL/REST APIs, and optimize performance across AI-enabled products.

You will work on semantic retrieval, embeddings, and vector search, while ensuring security, observability, and reliable CI/CD integrations. This is a distributed-first role with diverse work locations in the US.

Qualifications

• 7+ years of software engineering experience building and operating enterprise systems, APIs, or cloud-native products.
• Strong proficiency in TypeScript/JavaScript and modern front-end development with React; experience building accessible, responsive, and performant web applications.
• Hands-on experience designing or integrating MCP servers, tools, agent-facing APIs, or related context and agent frameworks.
• Demonstrated ability to apply distributed-systems principles, including concurrency, connection pooling, caching, retries, timeouts, backpressure, autoscaling, and load shedding.
• Experience measuring and improving latency, throughput, saturation, error rates, availability, token consumption, and end-to-end task cost.
• Practical experience with AI/ML evaluation and quality engineering, including benchmark design, groundedness, relevance, safety, hallucination detection, bias analysis, monitoring, and regression prevention.
• Knowledge of semantic search and retrieval systems, including embeddings, vector databases or indexes, hybrid retrieval, ranking, reranking, and permission-aware filtering.
• Experience integrating GraphQL, REST, JSON Schema, streaming APIs, SDKs, and event-driven systems into reliable product experiences.
• Proficiency in at least one additional systems or back-end language such as Python or Go, with strong testing and API design practices.
• Proven ability to lead cross-functional engineering initiatives, communicate clearly with technical and non-technical partners, and mentor other engineers.

Responsibilities

• Design, build, and evolve MCP servers, tools, and agent-facing APIs with concise schemas, predictable errors, safe mutations, and clear outcome-oriented contracts.
• Develop accessible, responsive, and performant React and TypeScript experiences that make agent capabilities, MCP tools, and A2A interactions easy to discover, configure, and use.
• Build reusable components, design-system patterns, and frontend architecture that support consistent, scalable user experiences across AI-powered products.
• Integrate GraphQL and REST APIs, SDKs, streaming responses, and real-time data into reliable, user-friendly AI workflows.
• Optimize token and context efficiency through dynamic tool discovery, lazy loading, bounded responses, pagination, selective field retrieval, caching, and reduced tool-call loops.
• Improve end-to-end performance and reliability across front-end clients, gateways, MCP servers, search services, and downstream product systems through observability, tracing, SLOs, and production diagnostics.
• Build semantic retrieval capabilities using embeddings, chunking, vector indexes, hybrid search, metadata and permission filters, ranking, reranking, and freshness strategies.
• Define and operate AI/ML quality programs with JTBD-based evaluations, benchmark datasets, groundedness and relevance metrics, hallucination and bias detection, safety testing, and human feedback.
• Integrate automated evaluations into CI/CD and release gates to detect regressions across model, prompt, tool, and retrieval changes.
• Implement enterprise security and partner cross-functionally to deliver maintainable, well-tested AI integrations, including OAuth 2.1, tenant isolation, audit logging, prompt-injection defenses, and confirmation flows for high-impact actions.

Skills

7+ years software engineering

TypeScript/JavaScript

React front-end

MCP servers / agent-facing APIs

Distributed systems

Latency/throughput optimization

AI/ML evaluation quality

Semantic search / embeddings

GraphQL / REST integration

Python or Go

Cross-functional leadership

Tools

GraphQL

REST

JSON Schema

Streaming APIs

SDKs

Job description

At Atlassian, join the Agentic AI Integrations team to design and build MCP servers, tools, and agent-facing APIs. You will craft scalable web experiences in React/TypeScript, integrate GraphQL/REST APIs, and optimize performance across AI-enabled products.

You will work on semantic retrieval, embeddings, and vector search, while ensuring security, observability, and reliable CI/CD integrations. This is a distributed-first role with diverse work locations in the US.