Senior Solutions Architect – Gen AI

This range is provided by HCLTech. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

$/yr - $/yr

We are seeking a Senior Generative AI Solutions Architect to lead the design and delivery of cutting‑edge GenAI‑driven solutions. This role is technology‑agnostic and strategically focused, requiring a blend of deep AI expertise, domain knowledge across different business verticals such as finance, healthcare, manufacturing, etc., and strong stakeholder management skills.

You will be responsible for structuring GenAI use cases, engaging with customers and internal teams, and orchestrating work across third‑party technology partners, all while ensuring secure, ethical, and regulatory‑compliant deployment of AI capabilities across the financial domain.

• Design end‑to‑end AI system architectures that integrate GenAI and Agentic capabilities into enterprise platforms.
• Build solutions around IT infrastructure for both on‑premise data centers and public cloud, thinking out of the box to deliver innovative Gen AI and Agentic AI solutions for large enterprise customers.
• Understand Gen AI and Agentic AI requirements across domains such as Financial Services, Health Care, Manufacturing, Automotive, Energy & Utilities.
• Evaluate and implement agent‑based orchestration frameworks (e.g., CrewAI, Auto Gen, Lang Graph).
• Lead the development of Retrieval‑Augmented Generation (RAG) pipelines and hybrid inferencing strategies.
• Serve as a technical advisor for responsible AI, model governance, and system explainability.
• Collaborate with data scientists and MLOps teams on model training, fine‑tuning, and deployment pipelines.
• Conduct architecture reviews and provide thought leadership on GenAI evolution, multi‑agent design patterns, and emerging tools.
• Present architectural visions and demo solutions to both technical and non‑technical stakeholders internal to HCLTech as well as customers.
• Select the right GenAI technologies (open‑source, proprietary, cloud, or hybrid) to meet client goals without vendor lock‑in.
• Lead solution blueprinting, technical feasibility assessments, and road‑mapping.
• Act as the primary GenAI thought leader in strategic client engagements.
• Conduct discovery sessions, co‑creation workshops, and presentations to business and IT stakeholders (including C‑suite).
• Translate complex AI capabilities into actionable business outcomes, ROI estimates, and transformation roadmaps.
• Deeply engage customers on Gen AI and Agentic AI solution articulation and secure their confidence.

• Strong advocacy of Responsible AI principles and experience building compliant solutions and platforms.
• Knowledge of key risk, compliance, and security procedures for Gen AI and Agentic AI solutions across multiple customers.
• Significant experience with governance of Gen AI and Agentic AI solutions.
• Proficiency in building guard rails for solutions and platforms on Gen AI and Agentic AI.

• Create reusable playbooks, frameworks, and GenAI solution kits specific to financial services.
• Mentor internal teams and conduct enablement sessions for business and technical stakeholders.
• Stay at the forefront of GenAI advancements, finance industry regulations, and AI risk trends.

• 15+ years in enterprise technology, consulting, or solution architecture roles, with 3+ years of hands‑on experience in GenAI or LLM‑based solution design.
• Deep expertise with LLMs (e.g., OpenAI, Mistral, Claude, LLaMA), embeddings, and vector DBs (e.g., FAISS, Pinecone).
• Expertise across a wide spectrum of GenAI technologies (e.g., OpenAI, Google Gemini, Anthropic, Meta Llama, Hugging Face).
• Strong communication skills with demonstrated experience engaging senior‑level stakeholders in both business and technology.
• Hands‑on experience with GenAI tools (Lang Chain, Llama Index, Transformers) and Agentic frameworks (Auto Gen, CrewAI, AutoGPT, etc.).
• Solid command of Python and cloud platforms (Azure, AWS, or GCP).
• Strong grasp of security, scalability, observability, and…