AI Solution Lead

Experience:

About the Role

AI Solution Lead

Key Responsibilities

Client Engagement & Requirement Analysis

• Engage directly with enterprise clients to understand business challenges, functional needs, and technical expectations.
• Translate high-level requirements into detailed solution blueprints, workflows, and technical specifications.
• Lead discovery workshops, requirement-gathering sessions, and solution walkthroughs.

Solution Architecture & Design

• Conceptualize AI-driven solutions, including LLM-based applications, multi-agent systems, document intelligence workflows, and data-centric applications.
• Create

  mockups, wireframes, user journeys

  , and high-level architecture diagrams to articulate solution ideas clearly.
• Evaluate feasibility, recommend architecture options, and define end-to-end solution strategy.

Proposal & Pre-Sales Support

• Prepare high-quality technical proposals, solution pitches, RFP responses, and effort estimations.
• Collaborate with sales, product, and engineering teams to craft value-driven propositions.
• Present solutions to CXO-level stakeholders, demonstrating strong communication and business articulation.

Project Delivery & Execution

• Own and manage the entire project delivery lifecycle—from planning, scoping, and execution to deployment and client handover.
• Collaborate with cross-functional teams: AI engineers, data scientists, UI/UX teams, product owners, and QA.
• Track progress, mitigate risks, manage dependencies, and ensure on-time, high-quality deliverables.
• Implement best practices in solution development, testing, integration, and deployment.

Integration & Multi-System Orchestration

• Lead projects that involve integration with multiple enterprise applications such as ERPs, CRMs, ticketing platforms, data warehouses, and custom APIs.
• Work with diverse stakeholders including IT, business operations, compliance, and vendor partners.
• Ensure security, authentication, authorization, and compliance standards are met.

Leadership & Collaboration

• Mentor AI engineers and solution analysts within the team.
• Drive innovation by contributing to solution accelerators, reusable components, templates, and knowledge assets.
• Support the AI engineering roadmap and collaborate with the product team to enhance platform capabilities.

Required Skills & Experience

• 10–15 years of total experience with strong exposure to solution design, enterprise system integration, and digital transformation projects.
• Hands-on understanding of generative AI concepts—LLMs, embeddings, vector stores, RAG, agents, workflow automation, and multimodal data processing will be good to have.
• Strong capability in solution design, system architecture, and creating mockups/wireframes.
• Proven experience in preparing proposals, crafting solution decks, and writing technical sections of RFP responses.
• Excellent communication skills with the ability to interact with senior stakeholders and cross-functional teams.
• Experience managing projects involving multiple applications and complex data flows.
• Familiarity with cloud platforms (Azure, AWS, GCP) and enterprise integration patterns.
• Strong problem-solving attitude and ownership mindset.

Preferred Qualifications

• Background in consulting, solution architecture, or technical program management.
• Certification in cloud or AI-related technologies is a plus.

Why Join Gapblue Software Labs?

• Opportunity to work on cutting-edge AI platforms and enterprise-grade solutions.
• Collaborative environment fostering innovation, learning, and continuous improvement.
• Chance to shape next-gen AI products and deliver impactful outcomes for global clients.