AI/ML and Data Engineering leader - Claude

Position: AI Engineer

Location: Charlotte, NC (Final Interview Onsite)

Interview Mode: Onsite Interview

Update: We are looking for a seasoned AI experience person with Claude Code experience. Not just Claude model usage alone.

Kindly source similar profiles with Claude Code experience. Thanks for your understanding and co-operation.

Key Responsibilities
• Experienced AI/ML and Data Engineering leader with 15+ years of software engineering experience and 5+ years building enterprise AI, Machine Learning, Generative AI, and cloud-native solutions. Strong hands-on expertise in designing and deploying production-scale AI platforms, RAG systems, AI Agents, MLOps frameworks, and cloud-native applications on AWS.
• Role Overview
• This role is primarily a 70% hands-on Individual Contributor and 30% technical leadership position. The engineer is expected to design, build, deploy, and optimize enterprise AI solutions while mentoring teams and coordinating with business, product, and engineering stakeholders.
• Key Responsibilities
• Build GenAI applications using OpenAI, Claude, Gemini, Llama, and AWS Bedrock. Develop RAG solutions, AI Agents, semantic search, prompt engineering frameworks, and MLOps pipelines. Create scalable APIs using Python and FastAPI. Design cloud-native architecture using AWS services and implement CI/CD automation.

Core Technical Skills
• Python, Java, SQL, Scala; OpenAI, Claude, Gemini, Llama, LangChain, LangGraph, RAG, AI Agents; SageMaker, Bedrock, Lambda, ECS, EKS, S3, DynamoDB, Redshift; Databricks, PySpark, Snowflake, Delta Lake, Kafka, Airflow; Docker, Kubernetes, Git, GitHub Actions, Jenkins, Terraform, CloudFormation.
• Infrastructure & DevOps
• Lead Infrastructure as Code implementations using Terraform and CloudFormation. Build automated deployment pipelines using Git-based workflows, CI/CD, containerization, Kubernetes orchestration, monitoring, logging, and governance controls.
• Leadership & Collaboration
• Provide architectural guidance, mentor engineers, conduct design reviews, support delivery planning, and collaborate with product managers, business stakeholders, compliance teams, and data scientists to deliver enterprise AI initiatives.
• Preferred Industry Experience
• Financial Services, Banking, Payments, Risk Analytics, Regulatory Reporting, Data Governance, and Enterprise Digital Transformation.
• Success Profile
• A highly technical practitioner capable of independently delivering AI solutions from concept to production while influencing architecture, standards, and engineering excellence across teams.