TECHNICAL LEAD - Java

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/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