AI Lead Engineer

Key Responsibilities:

• Design and implement

  AI/GenAI solutions

  aligned with client business requirements.
• Work directly with clients to

  understand business challenges and translate them into technical solutions

  .
• Lead

  AI solution discussions, technical presentations, POCs, and client workshops

  .
• Define the

  solution architecture, approach, success metrics, and implementation roadmap

  .
• Guide AI engineering teams and provide

  technical direction throughout the development lifecycle

  .
• Review and contribute to

  AI models, code, architectures, and technical implementations

  as required.
• Lead

  deployment, monitoring, optimization, and continuous improvement

  of AI solutions.
• Identify technical challenges and provide

  practical, scalable, and business-focused solutions

  .
• Collaborate with

  Data, Cloud, Software Engineering, and Business teams

  for end-to-end delivery.
• Support

  pre-sales, solutioning, proposals, and client presentations

  when required.
• Stay updated with emerging

  GenAI, LLM, Agentic AI, and AI engineering practices

  and recommend relevant solutions.
• Expertise in

  Azure AI services

  , including Azure OpenAI, Azure AI Services, and Azure ML.

Must-Have Qualifications:

• 8-12 years of overall experience with at least 4 years of experience in

  AI/ML, Data Science, Generative AI, LLMs, and NLP.
• Strong hands-on experience with

  RAG, Agentic AI, LLM applications, prompt engineering, and knowledge graphs

  .
• Experience with

  LangChain, Agentic AI frameworks, and orchestration tools

  .
• Proficiency in

  Python, Hugging Face, model fine-tuning, evaluation, and optimization

  .
• Strong understanding of

  vector databases, embeddings, and semantic search

  .
• Experience in

  AI solution architecture, POCs, deployment, monitoring, and productionization

  .
• Ability to

  translate business requirements into scalable AI solutions

  and define success metrics.
• Excellent

  client-facing communication and presentation skills

  , with the ability to explain complex AI concepts to technical and non-technical stakeholders.
• Experience in

  technical leadership, mentoring, and guiding AI teams

  .