Lead Software Engineer (Generative AI Java)

8 - 12 years

35 - 45 Lacs

Posted:1 week ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Principal or Lead Engineer

Responsibilities

  • Lead end-to-end architecture and implementation of Generative AI solutions integrated with Java-based applications
  • Evaluate, fine-tune, and deploy foundational and LLM models (e.g., GPT, LLaMA, Claude, Gemini) for use cases such as code generation, summarization, intelligent assistants, etc.
  • Collaborate with engineers and practice leads to identify and scope high-impact Gen AI use cases
  • Build solutions based on AI models with engineers. Mentor and guide junior engineers and set technical direction across AI initiatives
  • Build scalable APIs and microservices in Java/Spring Boot that interact with AI models
  • Optimize performance and cost of AI solutions in production using prompt engineering, retrieval-augmented generation (RAG), caching, and model selection
  • Contribute to AI model experimentation and evaluation pipelines (OpenAI, Hugging Face, LangChain, etc.)
  • Drive adoption of Gen AI best practices (e.g., guardrails, ethical AI, observability, and feedback loops)

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
  • 10+ years of experience in Java/J2EE/Spring Boot and backend architecture
  • 3+ years of experience working on ML/AI/Gen AI systems, including hands-on work with LLM APIs or open-source models
  • Strong knowledge of modern Gen AI frameworks likeLangChain, LlamaIndex, andVector DBs (e.g., FAISS, Pinecone, Chroma)
  • Experience integrating with LLMs via APIs (OpenAI, Azure OpenAI, Hugging Face) or self-hosted models
  • Working knowledge of Python for AI model orchestration and prototyping
  • Solid understanding of data pipelines, REST APIs, containerization (Docker, Kubernetes), and CI/CD workflows
  • Experience with AWS, GCP, or Azure AI/ML services

Nice to have

  • Familiarity with prompt engineering and fine-tuning LLMs using techniques like LoRA or PEFT
  • Experience building RAG-based chatbots, copilots, or AI-powered developer tools
  • Contributions to AI communities, research, or open-source Gen AI projects
  • Strong communication and stakeholder management skills

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