AI Solution Architect (Agentic & Generative AI)

Qualifications

• The candidate must demonstrate strong AI + AWS cloud expertise, with proven experience delivering enterprise-grade AI solutions in production environments

• Hallucination rates

• Python (primary)

• 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)

• 16 more items(s)

Responsibilities

• 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

• AI System Design & Development

• Design and build production-grade GenAI systems, including:

• 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

• Build and deploy multi-agent orchestration systems

• Develop and implement:

• Agent evaluation frameworks

• RAG evaluation pipelines

• Measure and optimize:

• Continuously improve models through evaluation-driven iteration

• Engineering & Platform Development

• Develop APIs and services using:

• Build scalable AI services with:

• REST APIs

• Microservices architecture

• Contribute to web-based AI applications using:

• 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

• 37 more items(s)

More job highlights

Job description

Dice is the leading career destination for tech experts at every stage of their careers.

Our client, Reveille Technologies, is seeking the following.

Apply via Dice today!

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

Role Overview

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.)

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