Java Tech Lead – Back-End & Agentic AI

We are seeking an experienced Java Tech Lead to join a cross-functional product team responsible for a customer-facing platform. You will lead the design and delivery of scalable, highly available back-end services while helping the team build secure, production-ready agentic AI capabilities.

This role requires robust technical leadership, hands-on Java expertise, solid architectural judgment, and close collaboration with Product, Front-End, Data/AI, Security, and SRE teams. You will guide engineering standards and technical decisions while remaining actively involved in design, development, and delivery.

What will you do?

- Lead the design, development, and evolution of scalable Java back-end services
- Build clean, maintainable, testable, and production-ready software
- Own technical and architectural decisions across services and integrations
- Design distributed systems, microservices, APIs, and event-driven workflows
- Develop agentic AI solutions that can reason, plan, use tools, access enterprise data, and execute multi-step workflows
- Integrate large language models using frameworks such as Spring AI, LangChain4j, or equivalent technologies
- Design retrieval-augmented generation (RAG), tool-calling, memory, and human-in-the-loop patterns
- Establish safeguards for AI systems, including access controls, data privacy, prompt-injection protection, output validation, and auditability
- Define evaluation approaches for AI quality, reliability, latency, safety, and cost
- Provide technical direction, mentoring, and constructive feedback to engineers
- Lead code reviews, design reviews, proof-of-concept initiatives, and knowledge-sharing sessions
- Collaborate closely with Product and business stakeholders to translate requirements into pragmatic technical solutions
- Ensure high standards for performance, availability, observability, security, and operational readiness
- Support and improve CI/CD pipelines, automated testing, and engineering delivery processes
- Participate in production support,



incident analysis, and continuous service improvement

Required knowledge and experience

- 10+ years of software engineering experience, including experience leading technical initiatives or engineering teams
- Strong hands-on experience with modern Java, preferably Java 17 or later
- Advanced knowledge of Spring Boot and the broader Spring ecosystem
- Experience designing and scaling microservice and event-driven architectures
- Strong understanding of object-oriented design, functional programming concepts, design patterns, and clean architecture
- Practical experience with Domain-Driven Design, CQRS, and Event Sourcing
- Experience building secure, resilient, and high-performance REST and/or GraphQL APIs
- Solid understanding of distributed systems, concurrency, fault tolerance, caching, and observability
- Hands-on experience with Kafka or similar event-streaming technologies
- Cloud-native development experience on AWS
- Experience with Docker, Kubernetes, and infrastructure-as-code practices
- Experience with relational and non-relational databases
- Strong knowledge of automated testing, including unit, integration, contract, and end-to-end testing
- Experience with CI/CD pipelines and modern software delivery practices
- Experience working in Agile, cross-functional product development teams
- Demonstrated ability to lead architectural discussions and communicate technical trade-offs clearly

Agentic AI knowledge and experience

- Practical experience building or integrating applications powered by large language models
- Understanding of agentic AI patterns, including planning, tool use, workflow orchestration, reflection, memory,



and multi-agent collaboration
- Experience with Spring AI, LangChain4j, or comparable AI application frameworks
- Knowledge of prompt engineering, structured outputs, function calling, embeddings, vector databases, and RAG
- Experience integrating hosted or self-managed models from providers such as OpenAI, Anthropic, AWS Bedrock, or open-source ecosystems
- Understanding of AI evaluation, hallucination mitigation, grounding, observability, and responsible AI practices
- Awareness of the security risks associated with LLM applications, including prompt injection, sensitive-data leakage, excessive agency, and unsafe tool execution
- Ability to balance model quality, latency, reliability, privacy, and cost in production systems

Preferred qualifications

- Experience/Knowledge with Python for AI services, experimentation, or data-processing workloads
- Experience with agent orchestration frameworks or durable workflow platforms
- Familiarity with vector databases and hybrid search technologies
- Experience with LLM observability, tracing, evaluation, and prompt-management platforms
- Knowledge of MLOps, model gateways, and AI governance
- Experience modernizing legacy Java platforms or guiding cloud migration initiatives
- Experience working in regulated, high-security, or high-availability environments

What will you bring as a colleague?

- A hands-on leadership style and a willingness to take ownership
- A critical-thinking mindset and the confidence to challenge assumptions constructively
- The ability to make pragmatic decisions while maintaining a strong long-term technical vision
- A growth mindset and a commitment to developing yourself and others
- Strong mentoring, facilitation, and stakeholder-management skills
- Curiosity about emerging AI technologies combined with sound engineering judgment
- A collaborative approach to solving complex technical and product challenges
- Excellent written and verbal communication skills in English

📌 TECHNICAL LEAD - Java (Bengaluru)
🏢 Happiest Minds Technologies
📍 Bengaluru