206590 - GenAI Architect
GenAI Architect
Location:
Iselin, NJ (Hybrid mode - Orion office)
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