AWS AI Engineer

Job Description

Job Description Job Title: AWS AI Engineer

Location: Remote / Hybrid (Hybrid candidates must be local to Charlotte, NC)
Duration: 6 Months
Experience: 12 Years

Job Summary

We are seeking an experienced AWS AI Engineer with strong expertise in Generative AI, Agentic AI, AWS Bedrock, Python, Prompt Engineering, and Advanced RAG Architecture. The ideal candidate will have hands-on experience designing and developing scalable AI solutions, autonomous agents, and enterprise-grade applications using AWS services and modern AI frameworks.

The candidate should be capable of owning technical modules, contributing to architecture and solution design, mentoring developers, and delivering high-quality solutions in an Agile/XP development environment.

Key Responsibilities

• Design, develop, and implement Generative AI and Agentic AI solutions using AWS services.

• Build advanced RAG architectures, LLM-powered applications, and autonomous AI agents.

• Develop reusable components, APIs, and MVP user stories.

• Work with AWS Bedrock, Agent Core Platform, AWS Strands, SageMaker, and other core AWS services.

• Design and optimize prompts, fine-tune models, and implement AI safety mechanisms.

• Contribute to technical architecture, solution design, and future-state technology direction.

• Work across application tiers, including development, APIs, databases, and data engineering.

• Support backlog creation, prioritization, and story mapping.

• Build and maintain CI/CD pipelines, including build and deployment jobs.

• Participate in pair programming, Test-Driven Development (TDD), and Extreme Programming (XP) practices.

• Take ownership of assigned modules, ensuring quality delivery and knowledge transfer.

• Mentor developers, troubleshoot technical issues, and support team members.

• Communicate effectively with technical teams and leadership.

Required Technical Skills Generative AI & Agentic AI

• Strong hands-on experience with Generative AI, Agentic AI, LLMs, and Prompt Engineering.

• Advanced RAG architecture and implementation experience.

• Experience with foundational models such as Anthropic Claude, Stability AI, and Llama variants.

• Knowledge of prompt engineering, fine-tuning, Spec-Driven Development (SDD), and AI safety mechanisms.

• Experience with LangChain and LlamaIndex for agent orchestration.

AWS Services

• Amazon Bedrock and Agent Core Platform.

• AWS Strands.

• Amazon SageMaker, S3, Lambda, and API Gateway.

• SQS, SNS, Step Functions, and CloudWatch.

• Redshift, Aurora PostgreSQL, Glue, and EMR.

• Strong understanding of AWS cloud architecture and service integration.

Programming & Data Engineering

• Advanced Python programming skills.

• Experience with Pandas, NumPy, Scikit-learn, PyTorch, and TensorFlow.

• Strong data engineering skills, including PySpark.

• Experience working with APIs, databases, and distributed data systems.

Vector Databases & RAG

• Experience with vector databases or RDS Vector Store.

• Knowledge of embeddings, retrieval mechanisms, and RAG optimization.

Engineering & Delivery

• Experience with DevOps and CI/CD pipelines.

• Strong understanding of TDD, XP practices, and pair programming.

• Ability to work independently and collaboratively.

• Strong problem-solving, communication, and mentoring skills.

Experience Requirements

• 12 years of overall experience in AI system design, Machine Learning, NLP, and software engineering.

• 1 2 years of hands-on experience in Generative AI or Agentic AI.

• Preferred experience: 12 15 years.

• Proven ability to own technical deliverables and mentor development teams.

Top 3 Required Skills

1. Agentic AI & Generative AI: Prompt Engineering, Advanced RAG Architecture, and LLMs.

2. AWS Cloud Services: Amazon Bedrock and core AWS services.

3. Programming & Data Engineering: Python and PySpark.