LTIMindtree is seeking a hands-on Full Stack AI Consultant to accelerate their AI in SDLC strategy. The role involves establishing agentic workflow orchestration capabilities and embedding modern engineering best practices across the organization.
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 Lang Graph including multiagent 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 CICD 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
- Handson experience orchestrating agentic AI workflows using Lang Graph Lang Chain or comparable frameworks
- Proven ability to design multiagent 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
- Excellent communication skills with the ability to influence from engineering teams to senior leadership
- Track record of delivering measurable outcomes within timebound engagements
- Insurance PC domain experience strongly preferred