Agentic AI Engineering Architect (Remote -US)

OMG Technology • Jersey City, NJ

1d • Remote

About The Position

We are looking to hire a candidate with the mentioned skill sets and experience for one of our clients within the pharmaceutical Industry. This is a REMOTE role. Lead the transformation of the software engineering organization into an AI-augmented, agentic engineering model. You will architect an enterprise framework that uses AI agents across the Product Development Life Cycle (PDLC) from requirements and architecture through development, testing, DevSecOps, release, and operations.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or related field; Master’s preferred.
• 12+ years of enterprise software engineering experience.
• 8+ years leading enterprise architecture initiatives.
• 5+ years leading cloud-native engineering transformations.
• Experience leading large Agile engineering organizations (200+ engineers preferred).
• Strong experience in enterprise software modernization and DevSecOps at scale.
• Strong understanding of Generative AI, Agentic AI, AI engineering platforms, and enterprise AI adoption.
• Experience implementing GenAI solutions in enterprise environments.
• Strong enterprise architecture, technical leadership, and organizational transformation skills.
• AI/Agentic AI: GenAI, LLMs, Agentic AI, RAG, Knowledge Graphs, LLMOps, AI Evaluation, AI Safety, MCP, Context Engineering.
• Engineering: Python, Java, C#, TypeScript, Node.js, React, REST/GraphQL, Microservices, Kubernetes, Docker, GitHub, Azure DevOps, Terraform, CI/CD.
• Cloud/Data: Azure, AWS, GCP, Databricks, Snowflake, PostgreSQL, Redis, Vector Databases, Neo4j.
• AI Frameworks: LangGraph, CrewAI, AutoGen, Semantic Kernel, PydanticAI, LangChain, LlamaIndex, OpenAI/Anthropic SDKs, Azure AI Foundry.

Responsibilities

• Define the AI-native SDLC / Agentic PDLC architecture and roadmap.
• Architect multi-agent workflows for requirements, architecture, development, testing, security, DevOps, compliance, and release management.
• Design the enterprise AI Engineering Platform/Harness, including LLM gateway, RAG, vector databases, knowledge graphs, MCP, agent registry, orchestration, memory, observability, and evaluation.
• Drive AI-enabled software engineering transformation, including AI coding, code review, automated testing, documentation, refactoring, and DevSecOps.
• Define enterprise architectures across cloud, microservices, APIs, data, event-driven systems, and AI infrastructure.
• Establish AI governance, security, Responsible AI, validation, and regulatory compliance practices.
• Lead enterprise AI adoption, engineering enablement, training, and change management.
• Evaluate and select AI platforms and frameworks such as OpenAI, Azure AI, AWS Bedrock, Google Gemini, Anthropic, LangGraph, AutoGen, Semantic Kernel, LangChain, MCP, GitHub Copilot, Cursor, and Claude Code.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior