Senior Software Engineer (Java / AWS / Agentic AI)
Job Description
The OperAxis team is seeking Senior Software Engineers (3 openings) for a 12-month contract with a heavy equipment manufacturing client in Chicago, IL (hybrid, 9:00 AM–5:00 PM). You will design and lead AI-native backend systems, building multi-agent workflows, RAG pipelines and Java microservices on AWS, while mentoring engineers and setting engineering standards across multiple teams. The ideal candidate has 8+ years of software engineering experience, 2+ years in a technical leadership role, and hands-on production experience with LLM-powered applications, AI agents and vector databases. Requirements: - Must have: AI, APIs, AWS, Java, LLM, Microservices and RAG - 8+ years of professional software engineering and 2+ years in a technical leadership role - Proven experience designing and delivering large-scale distributed systems - Deep backend expertise in Java, microservices architecture and API design - Experience with Docker, Kubernetes and AWS cloud-native infrastructure - Hands-on experience with production AI agents, prompt engineering and frameworks such as LangChain, LangGraph, AutoGen or CrewAI - Practical knowledge of vector databases (Pinecone, Milvus, Chroma or pgvector) - Fluency with AI coding assistants and a firm understanding of Model Context Protocol (MCP) - Knowledge of security architecture, application security and cloud security best practices - Strong communication, collaboration and stakeholder management skills - Bachelor's degree in Computer Science, Electrical Engineering or a related field Responsibilities: - Design and orchestrate multi-agent workflows and stateful AI systems - Integrate foundation models via secure API gateways, managing token limits, cost and rate limiting - Architect data models that combine relational and vector databases for semantic search and RAG - Implement testing and continuous evaluation to monitor AI outputs for accuracy, hallucinations and safety - Mentor engineers and establish standards for secure coding, CI and cloud-native deployment - Bring AI-assisted development tools into the team's daily SDLC and coach responsible AI use - Evaluate existing systems, APIs and data models for modernization and performance improvements - Lead architecture reviews, RFCs and technical forums with product owners, architects and engineering managers - Take part in all Scrum ceremonies and PR reviews, and drive automation that improves productivity and quality