Location: Noida / Chennai / Bangalore/ Pune/ Hyderabad
Experience: 10+ years
Position Overview
We are looking for a highly skilled and customer-focused AI Solution Architect to support Data & AI solutioning initiatives for enterprise customers. The role will be responsible for creating differentiated, scalable, secure, and business-aligned solution responses for RFPs, RFIs, RFQs, proactive proposals, client workshops, transformation engagements, AI adoption programs, and strategic deal pursuits.
The ideal candidate should have strong experience in Artificial Intelligence, Machine Learning, Generative AI, Agentic AI, enterprise AI platforms, MLOps, LLMOps, Responsible AI, AI governance, AI security, AI observability, and AI adoption at scale. The role requires the ability to translate client business requirements into compelling AI solutions, architecture narratives, technology recommendations, effort estimates, operating models, implementation roadmaps, and proposal-ready content.
This is an individual contributor role requiring strong solutioning, consulting, technical architecture, and stakeholder management capabilities across modern AI ecosystems on AWS, Microsoft Azure, and Google Cloud Platform.
Role Purpose
The AI Solution Architect will work closely with sales, presales, delivery, consulting, technology partners, and client stakeholders to define end-to-end AI, ML, GenAI, and Agentic AI solutions. The role will support business growth by shaping high-quality proposal responses, solution blueprints, architecture diagrams, AI adoption roadmaps, reusable solution assets, implementation approaches, and transformation narratives aligned to client business outcomes.
Key Responsibilities
- Lead and contribute to end-to-end presales solutioning activities for AI, ML, GenAI, Agentic AI, enterprise AI platforms, AI governance, and AI adoption opportunities.
- Analyze client RFPs, RFIs, RFQs, business requirements, current-state AI/data landscape, pain points, use cases, compliance needs, and evaluation criteria to design fit-for-purpose AI solutions.
- Create solution responses covering technical approach, target architecture, AI solution design, data and model architecture, integration approach, operating model, implementation roadmap, assumptions, dependencies, risks, and differentiators.
- Architect enterprise AI solutions covering machine learning, deep learning, natural language processing, computer vision, predictive analytics, recommendation engines, intelligent automation, GenAI applications, custom copilots, conversational AI, content intelligence, knowledge assistants, and Agentic AI workflows.
- Develop proposal-ready architecture narratives, logical architecture diagrams, AI reference architectures, solution flow diagrams, deployment views, AI operating model views, and technology stack recommendations.
- Support solution estimation by defining work breakdown structures, delivery phases, team composition, assumptions, dependencies, accelerators, and high-level effort inputs.
- Collaborate with delivery teams to ensure proposed AI solutions are practical, scalable, secure, compliant, implementable, and aligned with HCLTech delivery capabilities.
- Participate in client workshops, discovery sessions, AI ideation sessions, use case prioritization workshops, solution walkthroughs, technical presentations, and proposal defense discussions.
- Contribute to reusable assets, solution playbooks, reference architectures, estimation models, proposal templates, AI use case catalogs, GenAI patterns, governance frameworks, and industry-specific AI solution accelerators.
- Work with partner ecosystems including hyperscalers, foundation model providers, AI/ML platforms, data platforms, automation platforms, analytics platforms, and governance/security technology partners.
- Stay updated on emerging trends in Artificial Intelligence, Generative AI, Agentic AI, multimodal AI, responsible AI, AI governance, LLMOps, ModelOps, AI observability, AI testing, synthetic data, vector databases, RAG architectures, and enterprise AI adoption patterns.
Principal KPIs for the Role
- Contribution to strategic deal wins
- Quality and timeliness of RFP/RFI responses
- Customer solution acceptance and feedback
- Reusable solution assets/frameworks contributed
- Effectiveness of proposed AI architecture, AI governance, and AI adoption approach.
- Alignment of solutions to customer business outcomes, risk controls, compliance needs, and enterprise AI strategy.
- Innovation and value-added solution recommendations
Core Competencies & Technical Expertise
- Strong expertise in Data & AI solutioning and architecture for enterprise customers.
- Hands-on experience in preparing solution responses, architecture documents, presentations, technical proposals, AI strategy documents, operating models, and implementation roadmaps.
- Experience responding to RFPs/RFIs/RFQs and creating solution narratives, architecture diagrams, delivery approaches, AI adoption models, governance models, and estimation inputs.
- Strong understanding of modern AI ecosystems including Machine Learning, Deep Learning, Generative AI, Agentic AI, Natural Language Processing, Computer Vision, Predictive Analytics, Conversational AI, Intelligent Search, AI-infused BI, and AI-enabled automation.
- Experience with cloud platforms such as Microsoft Azure, AWS, and Google Cloud Platform, especially in the context of AI/ML, GenAI, data platforms, model deployment, observability, security, and governance.
- Strong understanding of cloud-native AI services across:
- Azure: Azure Machine Learning, Azure AI Foundry, Azure OpenAI Service, Azure AI Search, Azure AI Services
- AWS: Amazon SageMaker, Amazon Bedrock, Amazon Q, Amazon Comprehend, Amazon Textract, Amazon Rekognition, Amazon Transcribe, Amazon Translate, AWS AI governance/security services.
- GCP: Vertex AI, Gemini models, BigQuery ML, Document AI, Vision AI, Natural Language AI, Dialogflow
- Strong knowledge of AI architecture patterns including retrieval augmented generation, prompt engineering, fine-tuning, model evaluation, model selection, multi-agent workflows, human-in-the-loop review, AI orchestration, API integration, knowledge grounding, semantic search, and enterprise AI integration.
- Ability to define enterprise AI operating models including AI Center of Excellence, shared AI platform services, use case intake, prioritization, governance boards, adoption management, AI literacy, change management, and platform operations.
- Strong communication and presentation skills with experience interacting with customer stakeholders, CIO/CDO/CAIO organizations, business leaders, technology leaders, data teams, risk teams, and compliance stakeholders.
- Ability to work independently across multiple concurrent opportunities in a fast-paced presales environment.
- Strong analytical thinking, problem-solving, consulting, storytelling, and executive communication skills.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field.
- Preferred Certifications: Certifications across Azure AI, AWS AI/ML/GenAI, Google Cloud ML/AI, Databricks GenAI/ML, Snowflake GenAI, and Responsible AI/Governance are strongly preferred.
- Strong hands-on and architectural understanding of AI/ML platforms, GenAI solutions, model lifecycle management, cloud AI services, AI governance, MLOps, LLMOps, and enterprise AI adoption patterns.
- Experience in presales solutioning, proposal development, consulting, or customer-facing architecture roles is strongly preferred.
- Minimum 10 years of experience in Data & AI technologies, with relevant experience in AI architecture, ML engineering, GenAI solutioning, solution architecture, and presales solutioning.
