Responsibilities

- AI Strategy and Leadership:
- Define and execute AI strategies focused on RAG-based retrieval, code generation, and AI-assisted software engineering
- Work with stakeholders to align AI capabilities with business objectives and software development needs
- Research and integrate cutting-edge LLMs and autonomous AI agent architecture into development processes.

- RAG & Agentic AI Development:

- Develop RAG pipelines that enhance AI's ability to retrieve relevant knowledge and generate context-aware responses.
- Build and optimize agentic AI systems that can interact with APIs, databases, and development environments (such as LangChain, OpenAI APIs, etc.)
- Implement AI-powered search, chatbots, and decision-support tools for software engineers.
- Fine-tune LLMs (GPT, Llama, Mistral, Claude, Gemini etc.) for domain-specific applications.
- Optimize retrieval mechanisms to enhance response accuracy, grounding AI outputs in real-world data

- Code generation & Test case Automation:

- Leverage LLMs to generate high-quality, production-ready code
- Develop AI-driven test case generation tools that automatically create and validate unit tests, integration tests, and regression tests
- Integrate AI-driven code assistants and programming agents into IDE and CI/CD workflows
- Optimize prompt engineering and fine-tuning strategies for LLMs to improve code quality and efficiency

- MLOps & Scalable AI Systems:

- Architect and deploy scalable AI models and retrieval pipelines using cloud-based MLOps pipelines (AWS/GCP/Azure, Docker, Kubernetes)
- Optimize LLMs for real-time AI inferencing ,



ensuring low latency and high-performance AI solutions.

- Collaboration:

- Work cross-functionally with product teams, software engineers, and business stakeholders to integrate AI solutions into products.

- Mentorship:

- Guide and mentor a team of 3-5 AI engineers in LLM fine-tuning, retrieval augmentation, and autonomous AI agents.
- Establish best practices for AI-assisted software development, secure AI integration, and bias mitigation.

- Research & Innovation:

- Commitment to staying updated with the latest AI and machine learning research and advancements .
- Ability to think creatively and propose creative solutions to complex problems.

- Model Development:

- Ability to design, train, and evaluate various AI models , including LLMs and standalone models -familiarity with model training tools and frameworks like Hugging Face Trainer, Fairseq, etc.

Required Qualifications
- Education: Masters or Ph.D. in Computer Science, AI, Machine Learning, or a related field.
- Experience: 5+ years of experience in AI and machine learning, with at least 2 years of experience working on LLMs, code generation, RAG, or AI-powered automation .

Additional Information

This position requires a successful background and reference checks and satisfactory proof of your right to work in India. Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Sr Staff Engineer - AI Engineering (Pune)
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