Gen AI Architect

Remote • Posted 1 hour ago • Updated 1 hour ago
Contract W2
Contract Independent
2 Years
No Travel Required
Able to Sponsor
Remote
Depends on Experience
Company Branding Image
Fitment

Dice Job Match Score™

🔢 Crunching numbers...

Job Details

Skills

  • Azure AI Foundry
  • Agent365
  • Copilot
  • MS Purview
  • Defender
  • GenAI Architect
  • AI Architecture
  • Azure
  • MCP
  • Modernization
  • quality engineering
  • DevSecOps
  • SRE
  • Lead AI adoption
  • LLM
  • Agentic AI
  • security
  • privacy
  • data residency
  • auditability
  • multi-agent systems
  • Agent-to-Agent (A2A) interoperability
  • Model Context Protocol (MCP) servers and clients
  • AI gateways for routing
  • access controls
  • guardrails
  • cost governance
  • RAG
  • GraphRAG
  • context engineering
  • agent memory
  • agent frameworks
  • SDKs
  • AI coding assistants
  • autonomous agents
  • LLMOps
  • AWS Bedrock
  • Google Vertex AI
  • AI adoption

Summary

GenAI Architect

Location:

100% remote

Project Overview:

Join our dynamic Delivery department as a GenAI Architect, where you will play a key role in designing and implementing innovative solutions leveraging Generative AI, AI Architecture, and Transformation methodologies. With a focus on cutting-edge technologies like Azure and MCP, you will help shape robust AI-driven solutions for enterprise applications.

Modernization, quality engineering, DevSecOps, and SRE. 

Partnering with client executives, sector leaders, and delivery teams, you will translate AI strategy into production solutions and measurable business outcomes. Candidates must have personally designed, coded, and deployed production AI systems. 

Key Responsibilities:

  • Lead AI adoption: Co-create roadmaps aligned to client priorities; prioritize high-impact use cases and embed AI into end-to-end delivery workflows. 
  • Architect and build solutions: Design production-grade LLM applications and multi-agent systems with secure enterprise integrations, governed model access, and clear trade-offs across quality, latency, cost, and risk. 
  • Drive hands-on execution: Build rapid client PoCs, guide production deployment, debug agent behavior, review code, and establish reusable architectures and engineering standards. 
  • Design and architect Generative AI solutions tailored to enterprise needs, ensuring scalability and reliability.
  • Lead the integration of AI-related technologies within existing enterprise architecture frameworks.
  • Drive digital transformation initiatives by leveraging Agentic AI and innovative methodologies.
  • Develop and implement APIs to support seamless integration of AI-powered solutions across platforms.
  • Collaborate with cross-functional teams to define and refine solution architectures.
  • Ensure compliance with best practices and standards for enterprise and solution architecture.
  • Stay updated on emerging AI trends and technologies to incorporate them into architectural strategy.
  • Lead clients and teams: Advise senior stakeholders, enable changes in skills and ways of working, and lead forward-deployed engineers (FDEs) and AI specialists. Develop reusable assets, industry perspectives, and thought leadership. 
  • Embed responsible AI: Establish security, privacy, data residency, auditability, and human oversight controls appropriate to client and regulatory requirements. 

Required Skills and Experience:

  • Mandatory:
  • Proven AI transformation experience, including recent, personal delivery of production LLM applications and agents, preferably in regulated or security-sensitive environments. 
  • Deep AI architecture expertise spanning model selection, orchestration, data and context layers, identity, integration, and observability. 
  • Hands-on experience with multi-agent systems and Agent-to-Agent (A2A) interoperability, Model Context Protocol (MCP) servers and clients, and AI gateways for routing, access controls, guardrails, and cost governance. 
  • Strong practical knowledge of RAG, GraphRAG, context engineering, agent memory, and agent frameworks or SDKs; experience applying AI coding assistants and autonomous agents across the SDLC. 
  • Expertise in LLMOps, evaluation, regression testing, tracing, production monitoring, model adaptation, and inference optimization. 
  • Experience implementing defenses against prompt injection and tool misuse, human approval controls, and responsible AI governance. 
  • Hands-on experience with at least one major cloud AI platform—Azure AI Foundry, AWS Bedrock, or Google Vertex AI—and leading model-provider APIs. 
  • Strong executive communication, team leadership, and commercial judgment, with the ability to translate complex technology into compelling business value. 

Success in This Role:

  • Secure, scalable AI adoption that moves beyond experimentation, delivers measurable engineering and business improvements, and maintains continuity from strategy and deal commitments through production execution. 

AI Tools -

  • Azure AI Foundry 
  • Agent365
  • Copilot 
  • MS Purview
  • Defender
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 91172318
  • Position Id: 9130571
  • Posted 1 hour ago

Company Info

About Mind Ware Inc

Mind Ware Inc partners with organizations to support their technology hiring needs, with a focus on contract and project-based roles. We work on behalf of our client partners to source and place qualified technical professionals across a range of disciplines. Our team reviews resumes on an ongoing basis and connects candidates with opportunities that align with their skills, experience, and availability.

Contact the job poster
SV

Satya Vadlapatla

Recruiter @ Mind Ware Inc

Create job alert
Never miss an opportunity! Create an alert based on the job you applied for.