Java Tech Lead Developer with AI

We are seeking an experienced Java Technical Lead Developer with hands-on experience integrating AI/ML capabilities into enterprise applications. In this role, you will lead a team of engineers in designing, building, and scaling robust backend systems while driving the adoption of AI-powered features that enhance product functionality and user experience.

Required Qualifications

• Bachelor's or masters degree in computer science, Engineering, or related field
• 10+ years of professional software development experience with core focus on Java (Java 11+)
• 2+ years in a technical leadership or lead developer role
• Strong expertise in Spring Framework / Spring Boot, RESTful API design, and microservices architecture
• Proven experience integrating AI/ML models or services into production applications (e.g., calling LLM APIs, building RAG pipelines, embedding AI features into workflows)
• Familiarity with AI/ML concepts: prompt engineering, vector databases, embeddings, model inference, or MLOps
• Experience with relational and NoSQL databases (PostgreSQL, MySQL, MongoDB, etc.)
• Hands-on experience with cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes)
• Solid understanding of CI/CD pipelines, version control (Git), and automated testing
• Excellent problem-solving, communication, and stakeholder management skills

Job Description

We are seeking an experienced Java Technical Lead Developer with hands-on experience integrating AI/ML capabilities into enterprise applications. In this role, you will lead a team of engineers in designing, building, and scaling robust backend systems while driving the adoption of AI-powered features that enhance product functionality and user experience.

Required Qualifications

• Bachelor's or masters degree in computer science, Engineering, or related field
• 10+ years of professional software development experience with core focus on Java (Java 11+)
• 2+ years in a technical leadership or lead developer role
• Strong expertise in Spring Framework / Spring Boot, RESTful API design, and microservices architecture
• Proven experience integrating AI/ML models or services into production applications (e.g., calling LLM APIs, building RAG pipelines, embedding AI features into workflows)
• Familiarity with AI/ML concepts: prompt engineering, vector databases, embeddings, model inference, or MLOps
• Experience with relational and NoSQL databases (PostgreSQL, MySQL, MongoDB, etc.)
• Hands-on experience with cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes)
• Solid understanding of CI/CD pipelines, version control (Git), and automated testing
• Excellent problem-solving, communication, and stakeholder management skills

Preferred Qualifications

• Experience with AI/ML frameworks or tools such as LangChain, LlamaIndex, Spring AI, Hugging Face, or OpenAI APIs
• Familiarity with vector databases (Pinecone, Weaviate, Milvus, pgvector)
• Experience with event-driven architecture (Kafka, RabbitMQ)
• Exposure to Python for AI/ML prototyping and integration
• Understanding of responsible AI practices, data privacy, and model governance
• Experience in Agile/Scrum environments
• Relevant certifications (AWS Certified, Java certifications, AI/ML certifications)

Key Responsibilities

• Lead the design, development, and delivery of scalable, high-performance Java-based applications and microservices
• Provide technical leadership and mentorship to a team of developers, conducting code reviews and enforcing best practices
• Architect and implement integrations with AI/ML models and services (e.g., LLMs, recommendation engines, NLP pipelines) into existing Java applications
• Collaborate with data scientists and ML engineers to operationalize models into production-ready services
• Evaluate and integrate AI tools, APIs, and frameworks (e.g., OpenAI, LangChain, TensorFlow Serving, Spring AI) into the technology stack
• Drive technical decision-making on system architecture, design patterns, and technology selection
• Own the end-to-end software development lifecycle: requirements analysis, design, coding, testing, deployment, and maintenance
• Ensure application performance, security, scalability, and reliability
• Collaborate with cross-functional teams including Product, QA, DevOps, and Data Science
• Stay current with emerging AI technologies and assess their applicability to business use cases
• Contribute to technical documentation, coding standards, and engineering best practices
• Participate in sprint planning, estimation, and agile ceremonies