Tech Lead - AI/ ML/ GenAI

We are seeking a highly skilled and innovative Technical Lead (AI/ML/GenAI) with strong hands-on experience in Agentic AI, Machine Learning, and Cloud Platforms like AWS and Databricks. The ideal candidate will be proficient in building intelligent systems using agentic frameworks to deliver scalable, production-grade solutions such as chatbots and autonomous agents.

Key Responsibilities

• :Lead the design, development, and deployment of advanced machine learning models and algorithms for various applications
• .Build and optimize chatbots and autonomous agents using LLM endpoints and frameworks like LangChain, Semantic Kernel, or similar
• .Implement vector search using technologies such as FAISS, Weaviate, Pinecone, or Milvus for semantic retrieval and RAG (Retrieval-Augmented Generation)
• .Collaborate with data engineers and product teams to integrate ML models into production systems
• .Monitor and maintain deployed models, ensuring performance, scalability, and reliability
• .Conduct experiments, A/B testing, and model evaluations to improve system accuracy and efficiency
• .Stay updated with the latest advancements in AI/ML, especially in agentic systems and generative AI
• .Ensure robust security, compliance, and governance, including role-based access control, audit logging, and data privacy controls
• .Collaborate with data scientists, ML engineers, and product teams to deliver scalable, production-grade GenAI solutions
• .Participate in code reviews, architecture discussions, and continuous improvement of the GenAI platform

.Required Skills & Qualificatio

• ns8+ years of experience i

  n Machine Learning, Deep Learning, and AI system desi

  g
• n.Strong hands-on experienc

  e with Agentic AI frameworks and LLM APIs (e.g., OpenA

• I)Certifications in AI/ML or cloud-based AI platforms

  (AWS, GCP, Azu

  re
• ).Proficiency in Python and ML libraries like scikit-learn, XGBoost, et
• c.Experience with AWS services such as SageMaker, Lambda, S3, EC2, and IA
• M.Expertise in Databricks for collaborative data science and ML workflow
• s.Solid understanding of vector databases and semantic searc
• h.Hands-on experience with MLOps including containerization (Docker, Kubernetes), CI/CD, and model monitoring along with tools like MLflo
• w,Experience with RAG pipelines & LangChai
• n.LLM orchestration, or agentic framework
• s.Knowledge of data priva
• cyExposure to real-time inference systems and streaming dat
• a.Experience in regulated industries such as healthcare, biophar
• maProven ability to scale AI teams and lead complex AI projects in high-growth environmen
• tsOil & Gas, refinery operations & financial services exposure is preferr
• edMaster’s/ bachelor’s degree (or equivalent) in computer science, mathematics, or related fie