Gen AI Engineer ( ML )

Job Title:

Location:

Experience:

Roles & Responsibilities

• Lead the design, development, and deployment of GenAI applications using frameworks such as LangChain, LlamaIndex, HuggingFace Transformers.
• Architect and implement RAG pipelines, agentic systems, and MCP-based integrations.
• Drive QLoRA-based fine-tuning and quantization for domain-specific tasks.
• Ensure AI governance, compliance, and responsible use of generative AI solutions.
• Evaluate, benchmark, and integrate open-source and proprietary LLMs for enterprise-grade use cases.
• Collaborate with cross-functional teams including data engineers, backend developers, and product stakeholders.
• Mentor junior engineers, fostering growth in prompt engineering, model experimentation, and best practices.
• Stay ahead of emerging research and incorporate the latest advancements in LLMs, embeddings, multimodal models, and vector databases.
  

Required Skills

• 6+ years in software/ML engineering, with 2+ years focused on Generative AI.
• Deep expertise in RAG, MCP, agentic architectures, and LLMs.
• Strong proficiency in Python and leading AI frameworks (LangChain, LlamaIndex, HuggingFace).
• Proven hands-on experience with QLoRA fine-tuning and inference optimization.
• Solid knowledge of AI governance frameworks, compliance, and ethical AI practices.
• Familiarity with cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes).
• Exceptional communication and leadership skills, with the ability to mentor teams and articulate complex concepts clearly.
  

Preferred Qualifications

• Prior work with multi-agent systems, memory-based agents, or frameworks such as CrewAI, AutoGen, LangGraph.
• Experience with multimodal models (text-to-image/video/audio).
• Research publications or open-source contributions in the GenAI ecosystem.
• Demonstrated thought leadership in emerging AI technologies and enterprise adoption.