Software Development Engineer 3 - Java

About the Relay Team

At Relay, we are redefining test automation by building an AI-powered platform composed to deliver an outstanding experience across the entire software testing spectrum. Spanning functional testing (API, Web, Mobile, and Desktop) to non-functional testing (Performance and Chaos), our mission is to make quality engineering faster, smarter, and more reliable. We empower our team to build intelligent agents that author, complete, and self-heal tests, creating seamless solutions that transform how software quality is delivered at scale. If you are passionate about AI-driven innovation, engineering excellence, and elevating product quality, you’ll fit right in.

Role Description

We are looking for a Senior Backend Java Engineer to join the Relay team. In this role, you will design and scale high-volume backend applications, lead the integration of AI/ML capabilities into Java services, and build autonomous agents that drive next-generation test automation across core product teams.

Roles & Responsibilities

• Design and build high-volume, low-latency, and high-availability applications throughout the full software development lifecycle.
• Write clean, testable, specification-compliant code, managing software components through release.
• Integrate AI/ML capabilities, LLM APIs, and intelligent backend services (RAG, semantic search, automation) to power AI-driven workflows.
• Build AI agents for automated root cause analysis (RCA), self-healing, and intelligent test automation.
• Partner with Adobe product teams (e.g., Express, Firefly, Photoshop) to deliver end-to-end solutions, drive product adoption, and enable self-service platform engineering.
• Leverage AI-assisted tools (e.g., GitHub Copilot, Cursor) to accelerate development and support continuous architectural improvements.

Required Skills & Expertise

• Java Core & Frameworks: 5–8 years of experience building scalable, multithreaded server-side applications using Java/Java EE, Spring Framework, and object-oriented design patterns.
• Data & Performance: Deep proficiency with Relational Databases (SQL, high-performance transactional queries) and MongoDB, using ORMs (JPA2, Hibernate) optimized for speed and scalability.
• AI/ML Integration: Hands-on experience integrating LLMs/AI APIs (OpenAI, Claude, Gemini) into Java services using frameworks like Spring AI or LangChain4j, including prompt engineering and context management.
• AI Infrastructure & RAG: Familiarity with vector databases (e.g., Pinecone, Milvus, pgvector) and Retrieval-Augmented Generation (RAG) architecture to build reliable backend features.
• Modern AI Practices: Practical experience with AI-assisted dev tools (Copilot, Cursor) alongside an understanding of model deployment, cost/latency optimization, and responsible AI guardrails (privacy, hallucination mitigation).