Full Stack AI Consultant

Design and implement agentic workflow orchestration using LangGraph, including multi-agent collaboration, tool integration, memory management, and human-in-the-loop patterns. Define and execute an AI-in-SDLC strategy embedding intelligent automation across code generation, automated testing, code review, release notes, and deployment.

Our Client, an IT Services and Consultant company, is looking for a Full Stack AI Consultant for their Remote/Hybrid (Jersey City, NJ) location.
 
Responsibilities:

• Assess current engineering practices and deliver a prioritized modernization roadmap with AI integration at its core.
• Build Enterprise Shared Services and APIs that could be reused across different product teams
• Define and execute an AI-in-SDLC strategy embedding intelligent automation across code generation, automated testing, code review, release notes, and deployment.
• Design and implement agentic workflow orchestration using LangGraph, including multi-agent collaboration, tool integration, memory management, and human-in-the-loop patterns.
• Build reusable reference implementations, libraries, and playbooks for AI-augmented engineering.
• Drive adoption of DevOps, CI/CD, and observability practices with AI-driven enhancements.
• Advise on engineering policies and standards that embed AI-first principles.
• Upskill existing engineers on agentic AI patterns and AI-integrated development practices.

 
Requirements:

• 15+ years in software engineering with advisory experience.
• Expertise in Java, Spring Boot, Angular, and cloud-native architectures on Microsoft Azure.
• Strong background in microservices, Docker/Kubernetes, API-first design, and event-driven architectures.
• Hands-on experience orchestrating agentic AI workflows using LangGraph, LangChain, or comparable frameworks
• Proven ability to design multi-agent systems with tool use, planning, and RAG patterns.
• Experience embedding AI into the SDLC like AI-assisted coding, intelligent test generation, automated documentation, and release automation.
• Strong understanding of LLM orchestration, prompt engineering, and AI observability.
• Insurance P&C domain experience strongly preferred.
• Excellent communication skills with the ability to influence from engineering teams to senior leadership.
• Track record of delivering measurable outcomes within time-bound engagements.
• 18.00 Years of Experience

 
Why Should You Apply?

• Health Benefits
• Referral Program
• Excellent growth and advancement opportunities