Java Tech Lead Back-End & Agentic AI

Happiest Minds Technologies; Bengaluru; Presencial; INR 3.000.000 - 5.400.000; Jornada completa

Descripción de la vacante

Happiest Minds Technologies seeks a hands-on Senior Java Backend Architect to lead scalable back-end services in Bengaluru. You will own architectural decisions, design distributed systems, and drive AI-enabled workflows with LLMs and tool use.

You will mentor engineers, collaborate with product teams, and ensure high standards in performance, security, and observability, while advancing CI/CD delivery and production readiness.

Formación

• 10+ years of software engineering experience, including leading initiatives or 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, patterns, and clean architecture.

Responsabilidades

• Lead design, development, and evolution of scalable Java back-end services.
• Own technical and architectural decisions across services and integrations.
• Design distributed systems, microservices, APIs, and event-driven workflows.
• Develop agentic AI solutions that reason, plan, and execute multi-step workflows.
• Integrate LLMs using frameworks like Spring AI or LangChain4j.
• Mentor engineers and lead reviews and knowledge-sharing.

Conocimientos

Java 17

Spring Boot

Microservices

Distributed systems

Kafka

AWS

Docker

Kubernetes

CI/CD

Agile

Domain-Driven Design

CQRS

Event Sourcing

GraphQL

REST APIs

Observability

Security

LangChain4j

Herramientas

Java 17+

Spring Boot

Kafka

AWS

Docker

Kubernetes

LangChain4j

Descripción del empleo

Role & responsibilities

• 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

• 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 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