AI/ML Engineer – Generative AI & AWS

Job : AI/ML Engineer – Generative AI & AWS

Location: Reston, VA

Employment Type: Full-Time

Job Overview

We are seeking a highly skilled AI/ML Engineer with strong Generative AI and AWS expertise to design, develop, and deploy scalable, cloud-native intelligent solutions. The ideal candidate will have hands-on experience across the end-to-end machine learning lifecycle, including model development, deployment, and MLOps, along with practical exposure to LLM-based applications and RAG architectures.

Key Responsibilities

• Design and implement end-to-end AI/ML and Generative AI solutions using Python
• Develop, train, evaluate, and optimize machine learning models for production use
• Build and deploy LLM-powered applications such as chatbots, summarization tools, and semantic search systems
• Architect and implement RAG (Retrieval-Augmented Generation) pipelines, embeddings, and vector database integrations
• Develop high-performance Python microservices (FastAPI/Flask) for real-time inference and data processing
• Build and maintain cloud-native applications on AWS, leveraging services such as Lambda, ECS/Fargate, S3, API Gateway, DynamoDB, RDS/Aurora
• Utilize AWS AI/ML services including SageMaker and Bedrock for model development and deployment
• Implement CI/CD pipelines using GitHub, GitLab, or AWS CodePipeline for automated deployments
• Apply Infrastructure as Code (IaC) practices using Terraform or CloudFormation
• Establish and manage MLOps workflows, including model versioning, monitoring, retraining, and performance optimization
• Collaborate with cross-functional teams including data engineers, product managers, and business stakeholders

Required Skills & Qualifications

• Strong programming expertise in Python
• Hands-on experience with machine learning frameworks and model lifecycle management
• Proven experience with Generative AI / LLMs and RAG-based solutions
• Experience building APIs using FastAPI or Flask
• Strong experience with AWS cloud services (Lambda, ECS/Fargate, S3, API Gateway, DynamoDB, RDS/Aurora)
• Hands-on experience with Amazon SageMaker and/or Bedrock
• Experience with CI/CD pipelines and DevOps practices
• Proficiency in Infrastructure as Code (Terraform or CloudFormation)
• Strong understanding of MLOps practices including deployment, monitoring, and retraining

Preferred Qualifications

• Experience with vector databases (Pinecone, FAISS, Weaviate)
• Familiarity with LLM frameworks (LangChain, LlamaIndex)
• Experience with containerization (Docker) and orchestration tools (Kubernetes/EKS)
• Knowledge of real-time data processing and analytics systems