AI Engineering Consultant - LLM Models

Description :

AI Engineering Experience :

- 7 + years Location : Kochi/Hybrid

- This role requires a strong mix of technical depth, solution architecture, client requirement understanding, and end-to-end project delivery ownership.

- The consultant will work closely with clients, product teams, and engineering teams to ensure business requirements are translated into scalable, high-quality solutions.

- This is a hands-on, high-ownership technical and delivery role.

- Exposure to AI/Generative AI projects is a strong plus.

Key Responsibilities :

Technical Architecture & Solution Design :

- Own end-to-end solution architecture for client engagements.

Convert business and functional requirements into :

- Technical architecture

- System workflows

- Integration design

- Data and AI pipelines (where applicable)

- Define scalable, secure, and maintainable solution approaches.

- Review technical designs and guide implementation teams.

- Support architectural decisions across backend, frontend, integrations, and data layers.

End-to-End Project Delivery :

- Own complete delivery responsibility for assigned projects.

Work closely with engineering teams to ensure :

- Timely delivery

- Quality standards

- Performance and scalability

- Track milestones, dependencies, risks, and mitigation plans.

- Support UAT, production deployment, and post-go-live stabilization.

Client Requirement & Management :

- Work directly with clients to understand business problems and technical expectations.

- Conduct requirement discussions and solution workshops.

- Act as the technical interface between client and engineering teams.

- Provide technical walkthroughs, demos, and clarifications.

- Ensure alignment between client expectations and delivered solutions.

Product Thinking & Requirement Ownership :

- Apply product mindset while delivering client solutions.

- Convert requirements into :

- User stories

- Acceptance criteria

Technical tasks :

- Collaborate with internal product and platform teams to leverage Gapblue accelerators and reusable components.

- Support backlog grooming and sprint planning.

Agile Execution :

- Work within Agile / Scrum delivery models.

- Participate in sprint planning, reviews, and retrospectives.

- Help remove technical and requirement-level blockers.

- Ensure engineering teams have clarity on priorities and scope.

Required Skills & Experience :

Core Experience :

- 10 to 15 years of experience in software engineering and solution delivery.

- Strong experience as a Technical Architect / Solution Architect / Senior Technical Manager.

- Proven experience in end-to-end project delivery to enterprise clients.

- Prior experience playing a Product Ownerlike or Solution Manager role.

- Strong client-facing experience.

Technical Competencies :

- Strong understanding of system architecture and design patterns.

Experience with :

- Backend systems and API design

- Frontend and backend integration

- Workflow-based and data-driven systems

- Ability to review code and guide teams technically.

- Strong analytical and problem-solving skills.

Agile & Delivery Skills :

- Solid experience working in Agile projects.

- Ability to manage scope, timelines, and delivery dependencies.

- Experience working with multi-module or complex enterprise systems.

Good to Have :

- Experience working on AI/Generative AI/Data/Analytics projects.

- Exposure to LLM-based solutions, AI agents, or intelligent automation.

- Cloud exposure (AWS/Azure/GCP).

- Experience building reusable frameworks or enterprise platforms.

Personal Attributes :

- Strong ownership and accountability.

- Excellent communication skills.

- Ability to handle ambiguity and evolving requirements.

- Structured thinker with strong execution mindset.

- Comfortable working in fast-paced, client-driven environments.

Why Join Gapblue :

- Work on enterprise-scale AI and engineering solutions.

- High-impact role with deep technical involvement.

- Opportunity to work closely with AI platform and product teams.

- Exposure to multiple domains and real-world problem statements