Java + Python + AI Tech Champion

Happiest Minds Technologies; Bengaluru; Híbrido; INR 3 500 000 - 5 200 000; Tempo integral

Resumo da oferta

Happiest Minds Technologies is seeking an experienced Java Tech Lead to drive the back-end and agentic AI capabilities for a customer-facing platform. You will lead design, development, and delivery of scalable, highly available services while guiding architectural decisions and mentoring engineers.

The role collaborates with Product, Front-End, Data/AI, Security, and SRE teams to ship secure, production-ready software.

Qualificações

• 10+ years of software engineering experience including leading technical initiatives or teams
• Strong hands-on experience with modern Java (Java 17+).
• Advanced knowledge of Spring Boot and Spring ecosystem
• Experience designing and scaling microservices and event-driven architectures
• Understanding of object-oriented design, functional programming, patterns, and clean architecture
• Experience with Domain-Driven Design, CQRS, and Event Sourcing
• Building secure, resilient REST/GraphQL APIs
• Knowledge of distributed systems, concurrency, caching, observability
• Experience with Kafka or similar event-streaming technologies
• Cloud-native development on AWS
• Docker, Kubernetes, and infrastructure-as-code
• Relational and non-relational databases
• Automated testing (unit/integration/contract/e2e) and modern delivery
• Experience in Agile teams and architectural discussions
• Ability to communicate trade-offs clearly

Responsabilidades

• Lead design, development, and evolution of scalable Java back-end services
• Own technical and architectural decisions across services and integrations
• Guide engineering standards and technical decisions with hands-on involvement
• Design distributed systems, microservices, APIs, and event-driven workflows
• Develop agentic AI solutions with planning, tool use, and multi-step workflows
• Integrate large language models using frameworks like Spring AI or LangChain4j
• Design RAG, tool-calling, memory, and human-in-the-loop patterns
• Establish safeguards for AI systems and data privacy
• Define evaluation approaches for AI quality, reliability, latency, safety, and cost
• Provide technical direction, mentoring, and code/design reviews
• Lead architecture discussions and trade-off communications
• Collaborate with Product and stakeholders to translate requirements into pragmatic solutions
• Ensure performance, availability, observability, security, and operability
• Support CI/CD, automated testing, and engineering delivery processes
• Participate in production support and continuous service improvement

Conhecimentos

Java

Spring Boot

Microservices

Distributed systems

REST APIs

GraphQL

CI/CD

AWS

Docker

Kubernetes

Observability

Security

Leadership

Agile

Ferramentas

Kafka

Spring AI

LangChain4j

CI/CD tooling

Descrição da oferta de emprego

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 strong 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 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