AI Solution Architect Agentic & Generative AI

Hi,

Hope you are doing good.!

Position : AI Solution Architect – Agentic & Generative AI
Locations: Austin [Hybrid]

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.)