Description

Design and implement scalable AI/ML architectures for enterprise applications, leading Generative AI and LLM-based solutions.

This role is on-site.

Responsibilities

• Architect and optimize RAG pipelines, vector databases, and semantic search solutions.
• Define AI platform standards, governance, security, and Responsible AI practices.
• Design multi-agent orchestration frameworks and autonomous AI systems.
• Implement AI model lifecycle management including training, deployment, monitoring, and retraining.
• Establish MLOps and LLMOps best practices using modern CI/CD pipelines.

Required Skills

• 12+ years of IT experience with 5+ years in AI/ML architecture.
• Strong expertise in Generative AI, LLMs (GPT, Claude, Gemini, Llama), and Agentic AI frameworks (LangChain, LangGraph, AutoGen, CrewAI).
• Proficiency in Python, FastAPI, REST APIs, and Microservices.
• Experience with TensorFlow, PyTorch, Scikit-Learn, NLP, and Computer Vision.
• Strong knowledge of MLOps tools such as MLflow, Airflow, and Kubeflow.
• Hands-on experience with Docker, Kubernetes, Terraform, and CI/CD pipelines.
• Expertise in cloud platforms: Azure AI Studio, Azure OpenAI, AWS Bedrock, SageMaker, Google Vertex AI.

Preferred Skills

• Experience in multi-cloud environments (Azure, AWS, GCP) and enterprise AI transformation programs.
• Knowledge of AI governance, model explainability, and AI security.

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.

Key Skills

Education

Bachelor's degree