The ideal candidate will lead the technical delivery of AI initiatives, collaborate with cross-functional teams, and ensure scalable, secure, and production-ready AI systems.

Key Responsibilities :

- Design and implement scalable AI/ML architectures and production-ready solutions.

- Lead the development, deployment, and optimization of AI/ML models and LLM-based applications.

- Collaborate with Engineering, Data Science, and Product teams to deliver AI solutions.

- Build and manage MLOps/LLMOps pipelines, data workflows, and model deployment processes.

- Ensure AI systems meet performance, security, governance, and compliance standards.

Required Skills :

- 10+ years of software engineering/architecture experience with 5+ years in AI/ML.

- Strong programming skills in Python and experience with PyTorch, TensorFlow, or Scikit-learn.

- Experience with LLMs, RAG, Vector Databases (Pinecone, Weaviate, Qdrant), and LangChain/LangGraph.

- Hands-on experience with MLOps tools such as MLflow, Kubeflow, KServe, Airflow, or Argo.

- Experience with GCP or Azure AI services, Docker, Kubernetes, and Terraform.

- Excellent communication, technical leadership, and problem-solving skills.

Preferred Skills:

- Experience with Agentic AI, multi-agent frameworks (CrewAI, AutoGen), and AI governance/observability tools.

- Knowledge of Responsible AI, model monitoring, and regulatory compliance.