GenAI Lead

Job Overview:

We are seeking an innovative and highly skilled Lead Generative AI (GenAI) Engineer to spearhead the design, development, and deployment of advanced AI-powered solutions. In this role, you will lead a team of engineers and data scientists to harness cutting-edge Generative AI technologies and implement them to solve complex business problems, enhance user experiences, and drive innovation. This role combines deep technical expertise, leadership, and a strong understanding of AI trends and tools.

Key Responsibilities:

• Technical Leadership:
  • Lead the end-to-end design and implementation of Generative AI solutions.
  • Provide technical guidance and mentorship to engineers and data scientists working on GenAI projects.
  • Stay updated with the latest trends, research, and advancements in Generative AI and Large Language Models (LLMs).
• Solution Development:
  • Architect, train, and fine-tune state-of-the-art LLMs and generative AI models
  • Develop and optimize pipelines for prompt engineering, retrieval-augmented generation (RAG), and domain-specific fine-tuning.
  • Develop and deploy generative AI models, particularly focusing on ChatGPT, using Python on Azure or AWS Platform or .Net on Azure platform
  • Ensure scalability, performance, and security of AI solutions deployed in production.
  • Integration and Deployment:
• API Development:
  •  Ability to define and deliver API access for GenAI services, facilitating integration with other systems and applications.
  • Collaborate with software engineering teams to integrate GenAI solutions into enterprise applications and services.
  • Utilize cloud platforms (e.g., Azure, AWS, or GCP) to deploy and manage AI models and APIs.
  • Leverage MLOps practices for continuous model monitoring, retraining, and improvement.
• Data Strategy and Preparation:
  • Collaborate with data engineering teams to ensure high-quality data acquisition, preprocessing, and augmentation for model training and fine-tuning.
  • Implement data governance and privacy practices in line with organizational policies.
• Innovation and Research:
  • Experiment with new generative AI techniques, such as multimodal AI, reinforcement learning with human feedback (RLHF), and active learning.
  • Evaluate and recommend AI frameworks, libraries, and platforms for project requirements.
• Stakeholder Collaboration:
  • Work closely with product managers, business stakeholders, and UX designers to define AI-powered product features and use cases.
  • Present technical concepts, project progress, and AI capabilities to non-technical audiences.

Key Requirements

• Hands-on experience with cloud platforms and services for AI/ML, such as Azure AI Services, Azure Machine Learning, AWS Bedrock, or Google Vertex AI.
• Hands on experience in any of LLMs such as OpenAI’s ChatGPT Models , Gemini, Llama 2 ,Claude 2 ,Grok
• Hands on experience in any of the agentic frameworks like LangChain, Semantic kernel, AutoGen, CrewAi
• Hands on experience usi