Lead AI/ML Engineer - AWS Platform
First seen by Alion on Jul 31, 2026.
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
Skills
Artificial Intelligence, Machine Learning, RAG, AWS, AWS Bedrock, LLM, Agentic AI, Generative AI, Python, VectorDB