Data & AI Engineer

Role and Responsibilities

• Design, build, and deploy LLM-based APIs using Amazon Bedrock, supporting models like Claude, Titan, Nova, and Cohere
• Implement retrieval-augmented generation (RAG) pipelines using OpenSearch + S3
• Build data pipelines for curated and raw data layers using AWS Glue, Athena, and Lake Formation
• Support real-time reporting and AI usage dashboards via Amazon QuickSight
• Design serverless workflows using AWS Lambda and manage prompt metadata with DynamoDB
• Implement prompt orchestration strategies, including fallback handling, versioning, and safety guardrails
• Collaborate with product managers, architects, and DevOps to align AI/ML delivery with customer and project goals
• Document solutions clearly and support onboarding for handoff to client teams
• Stay current with AWS innovations in GenAI, MLOps, and scalable data platforms

Requirements

• Bachelor's or Master's in Computer Science, AI/ML, Data Science, or related field
• 5+ years of experience designing, building, and deploying cloud-based ML or GenAI systems
• Deep hands-on experience with AWS AI/ML services: Amazon Bedrock, AgentCore, SageMaker, Lambda, S3, DynamoDB, Glue, Athena, Lake Formation, OpenSearch, and QuickSight
• Strong Python development skills, with a focus on data manipulation, API development, and automation
• Experience implementing retrieval-augmented generation, prompt orchestration, or LLMOps workflows preferred
• Familiarity with CI/CD, Infrastructure-as-Code (IaC), and Git-based workflows
• Excellent communication skills and ability to explain AI system design and tradeoffs to both technical and business stakeholders in a client-facing, professional services environment

Benefits

• Paid Time Off
• Remote-First Working Environment
• Comprehensive Health Coverage
• 401(k) Retirement Plan
• Annual Learning & Development Stipend
• Peer Mentorship & Coaching
• Company Outings & Volunteer Opportunities
• Collaborative, Innovative Culture