Cloud Engineer- Data/AI Focused

As a Data & AI Engineer, you’ll build and deploy modern data pipelines and generative AI solutions on AWS — from scalable ETL/ELT workflows and cloud data platforms to production-grade RAG systems and AI agents. One engagement you may be designing and optimizing data pipelines using Glue, Lambda, and Redshift, the next you’re building GenAI applications powered by Bedrock, Claude, and vector databases to enable intelligent search and automation. You’ll work directly with clients to deliver end-to-end data and AI solutions that are secure, scalable, and production-ready.

What You’ll Do:

Implementing data pipelines using AWS services such as Glue, Lambda, Step Functions, and EMR

Creating and maintaining data extraction, transformation, and loading processes

Configuring and optimizing AWS database services including RDS, Aurora, Redshift, and DynamoDB

Implementing data lakes using S3 and related AWS services

Designing and building production-ready Generative AI applications using Amazon Bedrock and foundation models such as Anthropic Claude

Building and optimizing RAG (Retrieval-Augmented Generation) pipelines with vector databases

Developing AI agents and multi-agent orchestration systems using frameworks like LangChain or LlamaIndex

Writing and testing SQL queries and stored procedures

Documenting technical solutions and providing knowledge transfer to customers

Supporting the implementation of data governance and security controls

Troubleshooting and resolving issues with data pipelines and AI services

Participating in code reviews and implementing feedback

Assisting with proof-of-concept implementations for customer engagements

Required Skills:

5+ years of software engineering experience with at least 2+ years focused on AI/ML, data engineering, or cloud-native development

2+ years of hands-on AWS experience with production deployments

1+ years of direct Generative AI experience (LLMs, embeddings, RAG, agents)

Proven track record delivering production AI applications from concept to deployment

Strong understanding of software engineering best practices (version control, testing, code review, documentation)

Experience working in agile/scrum environments with distributed teams

Excellent problem-solving skills and ability to work independently with minimal supervision

Strong written and verbal communication skills for client-facing interactions

Preferred:

Technical familiarity with AWS data and AI/ML services and modern data engineering practices

Hands-on experience with ETL/ELT processes and data transformation

Exposure to Generative AI concepts including LLMs, embeddings, RAG, and agent frameworks

Ability to write and optimize SQL queries across various database platforms

Knowledge of data modeling concepts and best practices

Strong analytical and problem-solving skills

Eagerness to learn new technologies and keep up with cloud and AI innovations

Excellent communication skills with the ability to explain technical concepts clearly

Attention to detail and commitment to solution quality

Collaborative mindset with strong teamwork capabilities

Experience or interest in automation and infrastructure as code