Job Summary

The Solution Architect designs end-to-end architectures for AI, data, cloud platforms, AI-enabled applications, and enterprise workflows. The role translates customer requirements into scalable designs using OpenAI, hyperscaler and technology OEM ecosystems, and HCLTech capabilities while ensuring security, performance, compliance, Responsible AI, and delivery feasibility. The role produces reusable blueprints, solution artifacts, implementation guidance, and estimation assumptions that support strategic presales pursuits and transition into delivery.

Key Responsibilities

• Translate business and technical requirements into end-to-end architectures spanning AI, data, cloud, platforms, applications, integration, and operations.
• Define solution blueprints, integration patterns, deployment options, security controls, observability patterns, and non-functional requirements.
• Collaborate with engineering teams to validate feasibility, sequence delivery, identify risks, and define implementation guidance.
• Align solution designs to OpenAI, hyperscaler, technology OEM, and HCLTech product capabilities; ensure designs are reusable, scalable, and delivery-ready.
• Establish evaluation and guardrail requirements covering quality, safety, privacy, compliance, model behavior, and operational monitoring.
• Support presales and delivery teams with HLD/LLD inputs, architecture diagrams, effort estimates, assumptions, dependencies, and solution risk notes.
• Participate in customer workshops, technical deep dives, demo planning, and architecture review boards.
• Maintain reusable architecture blueprints and patterns for common AI use cases across industries and accounts.

Skill Requirements

• Strong AI/LLM fundamentals, including prompt engineering, embeddings, RAG, vector databases, agentic workflows, orchestration, model selection, and evaluation methods.
• Working experience with OpenAI or Azure OpenAI APIs, ChatGPT Enterprise use cases, OpenAI Codex or similar AI-assisted engineering tools, and hyperscaler AI services.
• Ability to architect secure enterprise AI solutions with data grounding, access controls, privacy controls, auditability, model observability, and human review loops.
• Experience designing POCs, pilots, prototypes, and production transition plans for AI-enabled applications or workflows.
• Ability to document Responsible AI controls, quality metrics, safety guardrails, and operational runbooks as part of solution design.

Other Requirements

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• 10+ years of experience in solution architecture, enterprise application architecture, data/cloud architecture, platform engineering, or presales solutioning.
• Strong AI/LLM fundamentals and experience translating requirements into scalable technical designs.
• Experience in value discovery, solution architecture design, POC/pilot/prototype development, and technical estimation.
• Strong customer-facing and communication skills with ability to explain complex architecture decisions simply.
• Technical leadership experience with engineering, delivery, or platform teams.
• Experience with workflow design, integration patterns, security, compliance, and non-functional requirement definition
• Experience with Azure, AWS, Google Cloud, enterprise integration, data platforms, DevSecOps, MLOps/LLMOps, or API management.

   

   

• Experience creating architecture diagrams, reusable solution blueprints, and bid response artifacts.

• Relevant cloud, AI, security, architecture, or data certifications