Senior AI Software Engineer

AI Software Engineer - Agentic SDLC (Java) Role Overview We are seeking an experienced AI Software Engineer with a strong Java background to design and implement Agentic AI capabilities across the software development lifecycle. This role will lead the development of AI agents and multi-agent workflows for requirements, architecture, code generation, testing, review, documentation, deployment, and modernization. The ideal candidate combines hands-on Agentic AI expertise with a strong foundation in enterprise software engineering and can translate engineering standards into secure, scalable, and production-ready AI workflows. Key Responsibilities Lead the design and implementation of Agentic AI capabilities that transform and accelerate the end-to-end SDLC. Architect autonomous and multi-agent workflows for requirements analysis, solution design, code generation, testing, code review, documentation, deployment, and support. Build enterprise AI agents using LangChain, LangGraph, AutoGen, CrewAI, or similar frameworks, including tool calling, orchestration, memory, and context management. Implement RAG, vector search, MCP integrations, structured outputs, and enterprise knowledge grounding to improve agent accuracy and relevance. Establish standards for prompt engineering, context engineering, spec-driven development, agent evaluation, and hallucination reduction. Define agent autonomy, decision boundaries, guardrails, human-in-the-loop approvals, security controls, and auditability for production environments. Configure and integrate agents with organizational coding standards, architecture patterns, engineering practices, repositories, CI/CD pipelines, and development toolchains. Required Qualifications 8+ years of software engineering experience, including strong proficiency in Java and enterprise application development. 2+ years of strong hands-on experience designing and building enterprise AI agents, multi-agent workflows, and GenAI-powered applications. Expertise with agentic frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar technologies. Experience implementing RAG, vector databases, tool calling, MCP integrations, memory, context management, and multi-agent orchestration. Advanced proficiency with AI development tools such as Claude Code, GitHub Copilot, Cursor, or similar platforms. Strong understanding of prompt engineering, context engineering, structured outputs, evaluation frameworks, guardrails, and hallucination reduction. Experience implementing AI-Augmented SDLC practices across requirements, architecture, development, testing, code review, documentation, deployment, and modernization. Ability to design autonomous and human-in-the-loop workflows for code generation, testing, debugging, documentation, and deployment. Experience reviewing and validating AI-generated code and agent outputs for correctness, security, maintainability, scalability, and performance. Understanding of responsible AI, enterprise governance, data privacy, access controls, secure agent execution, and auditability. Solid foundation in system design, object-oriented programming, data structures, algorithms, databases, APIs, concurrency, cloud platforms, and CI/CD. Bachelor's degree in Computer Science or a related field, or equivalent professional experience. Preferred Qualifications Experience with AWS, Azure, or Google Cloud Platform. Familiarity with secure coding practices and application security. Experience modernizing legacy enterprise applications using AI-assisted and agentic approaches. #J-18808-Ljbffr