Gen AI Lead

Job Title: Gen AI Lead
Location: Complete Remote
Type: Both Fulltime and Contract (C2C)
Experience in Yrs: 10 +Years

Job Description:
We are seeking an innovative and hands-on Generative AI Technical Lead to drive the design, development, and deployment of next-generation AI solutions. The ideal candidate will lead the creation of agentic AI automation agents, develop proof of concepts (PoCs) and minimum viable products (MVPs), and collaborate closely with business and technology stakeholders to turn AI innovation into measurable business value.

Key Responsibilities:
Lead the end-to-end development of proofs of concept and MVPs using Generative AI and large language models (LLMs).
Design, build, and deploy agentic AI automation agents capable of autonomous decision-making, task orchestration, and workflow automation.
Architect scalable and production-ready GenAI solutions leveraging advanced tools, frameworks, and APIs.
Collaborate with product, data, and engineering teams to identify high-impact AI use cases and define technical implementation paths.
Integrate GenAI models (e.g., OpenAI GPT, Claude, Gemini, Llama) and frameworks (e.g., LangChain, AutoGen, CrewAI) into enterprise products and services.
Foster alignment with stakeholders by converting technical innovation into actionable business outcomes.
Stay current with AI research and tools to continuously enhance solution capabilities.
Mentor engineers and data scientists in implementing AI agents, prompt design, and responsible AI development practices.

Required Qualifications:
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related discipline.
10+ years of overall experience in software engineering or AI solution delivery.
Proven hands-on experience in developing and deploying Generative AI models and AI agent frameworks.
Proficiency in Python and experience with AI/ML libraries such as PyTorch, TensorFlow, Hugging Face, and LangChain.
Familiarity with cloud platforms (AWS, Azure, Google Cloud Platform) and MLOps or AIOps practices.
Strong stakeholder management, communication, and leadership skills.
Ability to translate complex technical concepts into clear business insights and value propositions.

Preferred Qualifications
Experience with multi-agent orchestration tools (e.g., CrewAI, AutoGen, or similar).
Exposure to reinforcement learning, prompt engineering, and memory architectures for intelligent agents.
Background in building end-to-end intelligent automation workflows using AI orchestration platforms.
Knowledge of data privacy, security, and governance in AI applications.