Solution Architect

About the role

The Solution Architect serves as a technical advisor and AI-first solution strategist, bridging business requirements with technical delivery. This role works closely with sales teams during pre-sales engagements and provides architectural guidance to delivery teams throughout project execution. The architect is responsible for designing scalable, secure solutions that embed AI/LLM capabilities — including RAG, agentic workflows, and MCP-based integrations — across web, mobile, and enterprise platforms, while maintaining strong working knowledge of multi-cloud environments (AWS, Azure, GCP), project delivery, resourcing, and support escalation.

Key responsibilities

AI Solutioning & Innovation

• Architect end-to-end GenAI/LLM-powered solutions, including RAG pipelines, agentic workflows, and Model Context Protocol (MCP) based integrations, tailored to client business needs

• Design and refine system prompts and prompting strategies (few-shot, chain-of-thought, guardrail prompting) to optimize LLM output quality, safety, and cost

• Evaluate and recommend appropriate foundation models, AI frameworks, and orchestration tools based on use case, performance, and cost trade-offs

• Lead proof-of-concept and pilot development for AI capabilities (RAG, CAG, agentic assistants) to validate feasibility before full-scale implementation

• Establish best practices for responsible AI — guardrails, evaluation frameworks, hallucination mitigation, and monitoring of AI system performance

• Stay current with the fast-evolving AI/LLM landscape and evangelize emerging capabilities (new models, MCP tooling, agent frameworks) across the organization

Pre-Sales & Business Development Support

• Partner with sales teams to develop business opportunities and provide technical consultancy during customer requirement discovery sessions

• Translate business needs into conceptual solution architectures — including AI-enabled solutions — using the company's service portfolio

• Lead RFI/RFP responses, developing technical proposal content aligned with customer requirements

• Present technical and AI solutions to stakeholders at all levels, from technical teams to C-suite executives

Solution Design & Advisory

• Architect end-to-end solutions spanning web applications, mobile platforms, cloud infrastructure, and AI/ML integrations

• Evaluate emerging tools, techniques, and technologies (including new AI/LLM capabilities); conduct proof-of-concept implementations to validate feasibility

• Assess trade-offs between business needs, technology requirements, timelines, costs, and risks; communicate impact clearly to stakeholders

• Maintain architectural governance and ensure solutions (including AI solutions) align with enterprise standards, security, and best practices

Delivery Support & Issue Resolution

• Participate in client meetings alongside delivery teams to resolve technical issues during implementation and deployment

• Troubleshoot complex technical problems, including AI/LLM pipeline issues, performing root cause analysis and recommending corrective actions

• Provide ongoing architectural guidance to development teams throughout the SDLC

Project Management & Delivery Governance

• Support project planning, scoping, and effort estimation in collaboration with Project Directors/Managers

• Track technical delivery milestones and ensure alignment with agreed project timelines, budgets, and quality standards

• Identify and manage technical risks and dependencies, escalating proactively when delivery is at risk

• Contribute to sprint/iteration planning and backlog refinement from a solution architecture perspective

Knowledge Leadership

• Conduct technical training sessions, including on AI/LLM tooling and practices, to elevate organizational capabilities

• Drive technical knowledge harvesting and documentation of architectural patterns, AI solution designs, decisions, and lessons learned

• Mentor technical leads on solution design principles, including responsible AI adoption

Required Qualifications

• Bachelor's degree in Engineering, Computer Science, or related field (or equivalent work experience)

• Minimum 5+ years of experience across at least two IT solution development disciplines: technical/infrastructure architecture, application development, middleware, database management, or cloud development

• Hands-on experience designing or implementing AI/LLM-powered solutions (e.g., RAG systems, AI assistants, agentic workflows) is highly advantageous

• Proven track record in enterprise solution architecture with multi-cloud deployments

• AI/LLM Expertise: Hands-on proficiency with foundation models (GPT, Claude, Gemini, Llama), vector databases (Pinecone, Chroma, pgvector), agent frameworks (LangGraph, CrewAI), and LLM APIs.

• Cloud Platforms: Strong architectural experience across major cloud ecosystems, including AWS (Bedrock, SageMaker, Lambda, etc.), Azure (Azure OpenAI Service, AKS), and GCP (Vertex AI, BigQuery).

• Development & CMS Stack: Foundational working knowledge of languages and frameworks like React, Node.js, TypeScript, Flutter, native mobile, .NET, Java, and CMS platforms such as Drupal, WordPress, and AEM.

• Management Frameworks: Familiarity with Agile/Waterfall methodologies, ITIL support escalation processes, risk management, and cloud cost management (FinOps).