AI/ML Tech Lead - Generative AI

Job Description:

We are seeking an  AI/ML Tech Lead with strong hands-on experience in Generative AI to design and deliver production-grade LLM-powered solutions. This role focuses on building scalable GenAI systems on  Google Cloud Platform (GCP) , leveraging  Gemini models ,  RAG architectures , and  agentic workflows to solve complex business problems.

You’ll work closely with Data Science, Engineering, and Product teams to translate business needs into robust AI/ML solutions while ensuring performance, security, and compliance.

Key Responsibilities

• Design, build, and deploy  production-ready Generative AI applications and APIs on GCP.

• Implement  Retrieval-Augmented Generation (RAG)pipelines using vector databases and unstructured data sources.

• Develop and manage  end-to-end MLOps pipelines (training, evaluation, deployment, monitoring) using  Vertex AI, Kubeflow, Cloud Build, and Terraform .

• Optimize model performance through  fine-tuning, prompt engineering, and model compression techniques (e.g., GPTQ, AWQ).

• Architect scalable and cost-efficient GCP infrastructure with a strong focus on  security, IAM, and VPC design .

• Collaborate cross-functionally to define AI/ML technical roadmaps and deliver business-impacting solutions.

• Ensure adherence to  data privacy, security, and ethical AI standards (HIPAA, GDPR, where applicable).

• Provide technical leadership, guidance, and mentorship to team members.

Required Qualifications

• 5–8+ years of industry experience in Machine Learning.

• 3+ years of hands-on experience building and deploying  Generative AI / LLM-based solutions in production.

• Strong experience with  Google Cloud Platform (GCP) , including  Vertex AI, BigQuery, Dataflow, Cloud Run .

• Advanced proficiency in  Python and ML frameworks ( TensorFlow, PyTorch, scikit-learn ).

• Hands-on experience with  LLM frameworks/tools such as  LangChain, LlamaIndex, or Hugging Face .

• Solid understanding of  SQL and unstructured data processing.

• Experience with  Docker, Kubernetes (GKE), and CI/CD pipelines .

Preferred Qualifications

• Experience with  multi-agent systems and orchestration (LangGraph, AutoGen, etc.).

• Deep understanding of  vector databases (Vertex AI Vector Search, Pinecone, Chroma).

• Google Cloud Professional Machine Learning Engineer certification.

• Proven ability to  lead technical initiatives and mentor junior engineers.