AI Engineering Leader

AI Engineering Leader

Locations: Austin, TX | Charlotte, NC | New York, NY | Tempe, AZ | San Diego, CA, (hands on AI)

Role 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
.

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:
• Advanced AI orchestration frameworks (LangChain, LangGraph, etc.)