Description :

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 & Qualifications :

- 8+ years of experience in Machine Learning, Deep Learning, and AI system design.

- Strong hands-on experience with Agentic AI frameworks and LLM APIs (e.g.,OpenAI)

- Certifications in AI/ML or cloud-based AI platforms (AWS, GCP, Azure).

- Proficiency in Python and ML libraries like scikit-learn, XGBoost, etc.

- Experience with AWS services such as SageMaker, Lambda, S3, EC2, and IAM.

- Expertise in Databricks for collaborative data science and ML workflows.

- Solid understanding of vector databases and semantic search.

- Hands-on experience with MLOps including containerization (Docker, Kubernetes), CI/CD, and model monitoring along with tools like MLflow,

- Experience with RAG pipelines & LangChain.

- LLM orchestration, or agentic frameworks.

- Knowledge of data privacy

- Exposure to real-time inference systems and streaming data.

- Experience in regulated industries such as healthcare, biopharma

- Proven ability to scale AI teams and lead complex AI projects in high-growth environments

- Oil & Gas, refinery operations & financial services exposure is preferred

- Masters/ bachelors degree (or equivalent) in computer science, mathematics, or related field