Description :

As the Gen AI Lead, you will spearhead our organizations Generative AI strategy, moving beyond simple API integrations to build sophisticated, production-grade AI systems.

You will lead a cross-functional team of engineers and data scientists to architect Agentic AI frameworks, optimize RAG (Retrieval-Augmented Generation) pipelines, and ensure our AI solutions are ethical, scalable, and secure.

Key Responsibilities :

- Architecture & Design : Lead the design of multi-agent systems using frameworks like LangChain, AutoGen, or Semantic Kernel.

- Model Engineering : Oversee the fine-tuning of Large Language Models (LLMs) and Small Language Models (SLMs) using techniques like LoRA/QLoRA for domain-specific accuracy.

- LLMOps & Scalability : Establish robust deployment pipelines (CI/CD for AI), ensuring model monitoring, versioning, and cost-efficient scaling in the cloud (AWS/Azure/GCP).

- Governance & Ethics : Implement "Responsible AI" guardrails to mitigate hallucinations, bias, and data leakage, ensuring compliance with emerging AI regulations.

- Cross-Functional Leadership : Act as the primary technical SME for executive stakeholders, translating "AI hype" into measurable ROI and business outcomes.

Required Technical Skills :

- Core AI : Deep expertise in Transformer architectures, Diffusion models, and Vector Databases (e., Pinecone, Chroma, Milvus).

- Programming : Mastery of Python and frameworks like PyTorch or TensorFlow.

- Agentic Frameworks : Hands-on experience building autonomous agents and complex multi-step workflows.

- Data & RAG : Expert-level knowledge of chunking strategies, embedding models, and hybrid search techniques.

- Cloud & Infrastructure : Proficiency with Kubernetes, Docker, and AI-specific cloud services (e., Azure AI Foundry, AWS Bedrock, Google Vertex AI).

Experience & Qualifications :

- Experience : 8+ years in AI/ML, with at least 2 years specifically focused on Generative AI initiatives.

- Leadership : Proven track record of managing high-performing technical teams and delivering complex software products at scale.

- Communication : Ability to explain "black box" AI concepts to non-technical partners with clarity and authority.

Nice-to-Haves :

- Contributions to open-source GenAI projects or published research in the field.

- Experience with Multi-modal AI (Text + Image/Video/Audio).

- Certifications such as AWS Certified Machine Learning Specialty or Microsoft Azure AI Engineer Associate.