Senior AI Engineer Java Microservices & Agentic Development

Key Responsibilities

• Design and develop scalable Java/Spring Boot microservices, REST APIs, integrations, and event-driven services.
• Leverage Generative AI, LLMs, coding agents, Kiro, Agentic X, and similar tools to accelerate development.
• Translate business and technical requirements into effective prompts, specifications, and AI-assisted development tasks.
• Review, validate, debug, refactor, optimize, and productionize AI-generated code.
• Identify functional, architectural, security, performance, and maintainability issues in AI-generated solutions.
• Develop enterprise integrations using IBM MQ and Apache Kafka.
• Implement event-driven architectures, producers, consumers, queues, topics, and messaging patterns.
• Work with databases such as Oracle and MongoDB.
• Develop unit, integration, and component tests for both AI-generated and manually developed code.
• Integrate applications with CI/CD pipelines and DevOps processes.
• Collaborate with architects, engineering teams, and business stakeholders to deliver solutions rapidly and reliably.
• Continuously evaluate emerging AI development tools and contribute reusable prompts, accelerators, and AI-assisted engineering practices.

Core Java & Microservices

• 8+ years of software engineering experience with strong hands-on development expertise.
• Excellent proficiency in Java and Spring Boot.
• Strong experience designing and developing enterprise-grade microservices.
• Strong understanding of REST APIs, distributed systems, integration patterns, and microservices architecture.
• Strong debugging, problem-solving, coding, and software design skills.

• 3-5 years of relevant AI / AI-assisted engineering experience.
• Practical experience with Generative AI, LLMs, AI coding assistants, or agentic development.
• Hands-on experience using AI models and coding agents to accelerate software development.
• Experience with, or strong willingness to work with, Kiro, Agentic X, and other AI coding/agentic platforms.
• Ability to effectively provide context, requirements, and specifications to AI models.
• Strong ability to review, validate, debug, refactor, optimize, and secure AI-generated code.
• Understanding of AI-assisted SDLC across design, development, testing, documentation, and code review.

• Strong understanding of enterprise messaging and asynchronous integration.
• Hands-on experience with IBM MQ and Apache Kafka.
• Good understanding of event-driven architecture, queues, topics, producers, consumers, and messaging reliability patterns.

• Good understanding of CI/CD and DevOps practices.
• Experience integrating Java applications into automated build, testing, and deployment pipelines.
• Familiarity with Git, build tools, and automated deployment practices.