Full Stack AI Consultant

Job Title: Full Stack AI Consultant

Location: Jersey City (Hybrid) OR Remote

Job Type: Contract

Description:

Years of experience required: 15+

Mandatory skills:

Advisary and Hands on Experience implementing AI at Enterprise level, Agentic AI Orchestration skills, Java

Please note that there will be three levels of interviews (1 with Cognizant and 2 at client level)

JOB DESCRIPTION

We are seeking a hands-on Full Stack AI Consultant to accelerate our AI-in-SDLC strategy, establish agentic workflow orchestration capabilities, and embed modern engineering best practices across the organization Key

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.

Qualifications & Experience

· 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.