Gen AI Architect

Location: Bridgewater, NJ Persistent Office Full‑time only Experience: 12 to 15 Years What You'll Do Design & Implement Agentic AI Systems Architect and build multi‑agent, goal‑driven, autonomous AI systems using frameworks such as: AutoGen LangGraph CrewAI Create intelligent agent ecosystems supporting orchestration, reasoning, and collaborative task execution. Prompt Engineering & LLM Expertise Apply advanced prompt engineering techniques including: Few‑shot prompting Chain‑of‑thought reasoning Prompt templates Optimize prompt flows for deterministic, scalable LLM‑driven systems Cloud‑Native AI Architecture Design and deploy AI/LLM systems on cloud platforms such as AWS Bedrock, Azure OpenAI, Google Vertex AI, etc. Ensure solutions meet enterprise NFRs including performance, security, cost‑optimization, and availability. RAG Pipelines, Vector Databases & MCP Architect and deploy RAG pipelines using vector databases such as: Pinecone Weaviate ChromaDB

FAISS

Implement MCP Servers and Agent‑to‑Agent (A2A) communication frameworks. LMOPs / GenAIOPs Implement end‑to‑end operational pipelines for GenAI applications including: Continuous integration & deployment Model monitoring & drift detection Logging, observability, and troubleshooting mechanisms Establish governance models, reusable patterns, and GenAI best practices. Application & Microservices Architecture Design microservices‑based systems using Spring Boot, REST APIs, and secure API design patterns. Implement API security, versioning, and distributed system governance. Architect cloud‑native applications using AWS/Azure/Google Cloud Platform, Spring Cloud, PCF, or equivalent. Collaboration & Leadership Work closely with Data Scientists, Product Owners, Business SMEs, and Engineering teams. Lead end‑to‑end solution architecture for enterprise AI initiatives. Conduct technical presentations, architectural reviews, and stakeholder communication. Expertise You'll Bring 5+ years in software/solution architecture. Proven experience as a Data Scientist or ML Engineer with exposure to agentic AI systems. Experience designing multi‑agent systems using AutoGen, LangGraph, CrewAI, etc. Strong understanding of cloud AI platforms (Bedrock, Azure OpenAI, Vertex AI). Hands‑on experience with AI Code Assist tools such as: GitHub Copilot Windsurf Cursor

AWS Q

Expertise in Vector Databases, RAG pipelines, MCP, and multi‑agent communication. Strong proficiency in Python (preferred), and optionally Java/Node.js. Experience with microservices, Spring Boot, REST APIs, API security, and versioning. Proficiency in Docker, Kubernetes, CI/CD pipelines. Strong grasp of design patterns and architecture principles. Deep understanding of cloud‑native design and distributed systems. Experience designing AI systems that meet NFRs: scalability, security, performance, maintainability. Exceptional communication and presentation skills. Ability to articulate complex AI concepts to technical and non‑technical audiences. Strong leadership, problem‑solving mindset, and strategic thinking abilities. Ability to collaborate with cross‑functional teams to translate business needs into AI‑powered solutions. #J-18808-Ljbffr Compugra Systems Inc