Overview: We are seeking a highly hands-on AI Engineering leader with deep expertise in Generative AI, Agentic systems, and production-grade AI platforms. This role is not a pure management role — the ideal candidate will actively design, build, and scale AI systems (RAG, agents, evaluation frameworks) while leading engineering initiatives and influencing platform strategy. The candidate must demonstrate strong AI + AWS cloud expertise, with proven experience delivering enterprise-grade AI solutions in production environments.
AI Engineering Leader
Locations: Austin, TX | Charlotte, NC | New York, NY | Tempe, AZ | San Diego, CA, (hands-on AI)
Long-term Contract
Core Responsibilities
AI System Design & Development
- Design and build production-grade GenAI systems, including:
- Multi-agent architectures
- Retrieval-Augmented Generation (RAG) pipelines
- GraphRAG implementations
- Autonomous agent workflows and orchestration
- Develop and integrate AI agents with tools, APIs, and enterprise systems
- Implement MCP-based agent communication and tool-use frameworks
- Apply advanced prompt engineering techniques for reliability and performance
Agentic AI & Evaluation
- Build and deploy multi-agent orchestration systems
- Develop and implement:
- Agent evaluation frameworks
- RAG evaluation pipelines
- Measure and optimize:
- Output quality
- Hallucination rates
- Relevance and groundedness
- Continuously improve models through evaluation-driven iteration
Engineering & Platform Development
- Develop APIs and services using:
- Python (primary)
- .NET (preferred)
- Build scalable AI services with:
- REST APIs
- Microservices architecture
- Contribute to web-based AI applications using:
- Angular / TypeScript (preferred)
- Integrate AI systems into enterprise workflows and applications
Cloud & Infrastructure (AWS Focus)
- Design and deploy AI solutions on AWS, leveraging:
- Lambda, S3, EC2, EKS, Glue, SNS, SQS
- Kafka-based streaming architectures
- Build scalable and secure AI pipelines using cloud-native patterns
- Implement cost-efficient and high-performance AI workloads
DevOps & CI/CD
- Design and implement CI/CD pipelines using GitHub Actions
- Integrate AI workflows into CI/CD pipelines with strong AWS integration
- Ensure:
- Automated deployment
- Testing and validation of AI systems
- Continuous monitoring and iteration
AI Development Tooling
- Leverage modern AI development tools and ecosystems, including:
- Claude (Claude API / Claude Code)
- Cursor AI (AI-assisted development workflows)
- Build and optimize developer workflows using AI-assisted coding tools
Required Qualifications
- 10+ years of overall engineering experience
- 5+ years of hands-on AI/ML / GenAI development in production environments
- Strong experience building:
- AI agents (minimum 2+ implementations)
- GraphRAG systems (minimum 2+ implementations)
- MCP-based integrations (minimum 1+)
- Proven expertise in:
- Multi-agent orchestration
- RAG pipelines
- Agent and RAG evaluation frameworks
- Strong programming skills in:
- Python (must-have)
- Experience with:
- API development and system integration
- Strong experience with:
- AWS cloud platform (must-have)
Preferred Qualifications
- Experience with:
- .NET / C# development
- Terraform (Infrastructure as Code)
- Experience building:
- Web applications using Angular / TypeScript
- Familiarity with:
- Kafka-based streaming systems
- Exposure to:
