Java Tech Lead Back-End & Agentic AI

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

Perks and benefits

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