Sr Staff Engineer - AI Engineering

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 innovative 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


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