Senior AI/ML Engineer Lead (AWS & Generative AI)

Role: Senior AI/ML Engineer Lead (AWS & Generative AI)

Remote with Initial Few Weeks Hybrid ( Nashua, NH)

Full Time Only

Experience Level-: 10-15 Years

Role Overview

We are seeking a highly skilled Senior AI/ML Engineer with deep expertise in AWS AI/ML services and a strong understanding of Generative AI using Amazon Bedrock. The ideal candidate will have hands-on experience building, deploying, and optimizing AI/ML models on AWS, integrating LLMs into real-world applications, and implementing scalable AI pipelines.

Key Responsibilities

• Design, develop, and deploy AI/ML models on AWS using SageMaker, Bedrock, and related services.
• Build LLM-based applications and fine-tune models for domain-specific use cases.
• Implement RAG (Retrieval-Augmented Generation) pipelines with vector databases such as OpenSearch, Pinecone, or FAISS.
• Develop production-ready ML pipelines leveraging AWS services including Lambda, Step Functions, S3, and DynamoDB.
• Integrate ML models into real-world applications in collaboration with cross-functional teams.
• Ensure AI solutions align with best practices in security, compliance, and cost optimization.
• Stay current with the latest advancements in Generative AI, prompt engineering, and model optimization.

Required Skills & Experience

• Strong expertise in AWS AI/ML stack: SageMaker, Lambda, Step Functions, S3, DynamoDB, etc.
• Proven experience with Generative AI models (GPT, Claude, Mistral, LLaMA, etc.) and fine-tuning techniques.
• Hands-on programming experience with Python, TensorFlow, PyTorch, and Hugging Face.
• Knowledge of vector databases and embedding models.
• Experience in building secure, scalable AI solutions on AWS.
• Familiarity with MLOps practices, CI/CD pipelines, and cloud automation.
• Strong analytical and problem-solving skills with the ability to work in a fast-paced environment.

Good to Have

• Experience with LangChain, Prompt Engineering, and RAG techniques.
• Understanding of data governance, AI ethics, and responsible AI practices.
• AWS Certifications: Machine Learning Specialty / Associate or other relevant AI certifications.