AI Solution Architect – Agentic & Generative 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.)