Job Summary :

We are looking for an experienced Lead AI/ML Engineer to design and build scalable AI/ML solutions using AWS SageMaker, Amazon Bedrock, RAG architectures, and AI agents.

The ideal candidate should have strong hands-on experience in designing data foundations for AI workloads, integrating foundation models, and fine-tuning AI/ML solutions for enterprise use cases.

Key Responsibilities :

- Design and develop robust data foundations to support AI/ML workloads using Amazon SageMaker and Amazon Bedrock.

- Architect and implement Retrieval-Augmented Generation (RAG) solutions for enterprise AI applications.

- Design scalable and production-ready AI/ML pipelines and infrastructure on AWS.

- Work with Amazon Bedrock foundation models and implement effective model integration strategies.

- Develop and integrate AI agents using Agent Core and related agentic AI capabilities.

- Implement and optimize Claude-based AI solutions, ensuring effective model integration and performance.

- Identify suitable AI/ML workloads and use cases based on business requirements and technical feasibility.

- Fine-tune and optimize AI/ML models to improve accuracy, performance, latency, and cost efficiency.

- Evaluate different foundation models and AI/ML approaches and recommend the most appropriate solutions.

- Develop scalable architectures for LLM, Generative AI, and agentic AI applications.

- Work closely with data engineering, software engineering, cloud, and business teams to translate requirements into AI/ML solutions.

- Establish best practices around model evaluation, prompt engineering, RAG performance, security, governance, and responsible AI.

- Monitor AI/ML solutions in production and continuously identify opportunities for optimization and improvement.

- Provide technical leadership, conduct architecture reviews, and mentor team members on AI/ML and Generative AI technologies.

Required Skills & Experience :

- Strong experience in AI/ML engineering and solution architecture.

- Hands-on experience with AWS SageMaker and Amazon Bedrock.

- Strong understanding of Generative AI, Large Language Models (LLMs), and RAG architectures.

- Experience working with Agent Core / agentic AI frameworks.

- Strong experience integrating and working with Claude models.

- Experience with AI/ML model fine-tuning, optimization, and evaluation.

- Strong understanding of data pipelines and data foundations required for AI/ML workloads.

- Experience designing scalable and production-ready AWS-based AI/ML architectures.

- Strong programming skills in Python.

- Experience with vector databases, embeddings, semantic search, and knowledge retrieval is highly desirable.

- Understanding of MLOps/LLMOps, model monitoring, deployment, and lifecycle management.

- Strong knowledge of cloud security, data privacy, and governance principles for AI/ML workloads.

Leadership & Soft Skills :

- Strong technical leadership and architecture capabilities.

- Ability to evaluate emerging AI technologies and translate them into practical business solutions.

- Excellent problem-solving and analytical skills.

- Strong communication and stakeholder-management abilities.

- Ability to mentor engineers and drive engineering best practices.

Key Technologies :

- AWS : SageMaker, Amazon Bedrock

- GenAI : LLMs, RAG, Agentic AI, Claude

- AI/ML : Model Fine-Tuning, Model Evaluation, MLOps/LLMOps

- Programming : Python

- Architecture : AI/ML Data Foundations, RAG Architecture, AI Agents