What are the responsibilities and job description for the AI Deployment Engineer position at Yotta Systems INC?
Position: AI Deployment Engineer
Location: Charlotte, NC (Hybrid 3 days onsite / 2 days remote)
Type: Contract
Client: Synechron Wells Fargo
Job Summary
We are looking for an experienced AI Deployment Engineer/Lead with 12 13 years of IT experience and a strong client-facing background. The ideal candidate should have proven experience in end-to-end deployment of AI/GenAI applications, including solution design, integration, deployment, and production rollout. The role requires close collaboration with business stakeholders and technical teams to deliver enterprise AI solutions.
Key Responsibilities
- Lead the end-to-end rollout and scaling of GenAI tools (Devin, Claude Code, Cursor) across engineering teams.
- Build and integrate full-stack solutions into enterprise SDLC workflows, including CI/CD pipelines, repositories, and APIs.
- Define and execute enterprise-wide rollout strategies and phased onboarding plans.
- Partner with business and engineering teams to enhance the software delivery lifecycle using GenAI.
- Conduct developer onboarding, training, and enablement sessions focused on prompt engineering and AI workflows.
- Monitor adoption, usage metrics, and tool performance while driving continuous improvements.
- Troubleshoot, optimize, and scale AI-enabled engineering solutions.
- Establish reusable playbooks and best practices for enterprise GenAI adoption.
- Ensure compliance with enterprise governance, security, and regulatory standards.
Required Skills
- Strong Full Stack Development experience with:
- Java
- Python
- React / Angular / TypeScript
- Experience with:
- Distributed Systems
- Microservices and Event-Driven Architectures
- API Design and Integration
- Hands-on experience with:
- CI/CD Pipelines
- Developer Tooling Ecosystems
- Cloud Platforms:
- OpenShift (OCP)
- Google Cloud Platform (Google Cloud Platform)
GenAI / LLM Experience
Hands-on experience with:
- Devin
- Claude / Anthropic Models
- Cursor or similar AI coding assistants (GitHub Copilot, etc.)
Strong understanding of:
- Prompt Engineering
- RAG (Retrieval-Augmented Generation)
- Agent-Based Workflows
- Multi-Agent Architectures
- MCP (Model Context Protocol)
- Agentic AI, Tool Chaining, and Autonomous Workflows
Preferred
- Experience working in enterprise environments with governance and compliance.
- Strong stakeholder communication and collaboration skills.
- Ability to translate business requirements into technical solutions.
- Passion for driving AI adoption and improving developer productivity.
Salary : $70