SENIOR AI SOLUTION ARCHITECT

Responsibilities

1. Lead end-to-end AI solution architecture and technical solutioning for enterprise opportunities.
2. Translate customer business requirements into secure, scalable, responsible and commercially viable AI solutions.
3. Lead customer discovery, AI strategy workshops, demonstrations, architecture reviews, use-case assessments and proof-of-concepts.
4. Develop AI solution architectures, HLD/LLD, data-flow designs, sizing, BoM, costing, implementation roadmaps and proposals for RFI/RFP/tenders.
5. Design solutions across generative AI, LLMs, machine learning, computer vision, NLP, intelligent automation, conversational AI, agents and predictive analytics.
6. Architect enterprise AI platforms across public, private and hybrid cloud, including data platforms, training, fine-tuning, inference, RAG, vector databases, APIs and MLOps/LLMOps.
7. Establish secure and responsible AI architectures covering privacy, IAM, governance, explainability, bias, content safety, compliance, auditability and human oversight.
8. Work closely with Sales, Product, Engineering, Delivery, Managed Services, Cybersecurity, Legal, Finance and Bid Management to ensure technically sound, deliverable and commercially competitive solutions with healthy margins.
9. Evaluate AI technologies; build reusable architectures and best practices; engage technology partners; lead commercial and delivery transition risks; define success measures and production operating processes.

Requirements

• More than 8 years in business analysis, solution architecture, data, software engineering or enterprise AI and cloud workflow solutioning, with strong business acumen and interpersonal skills.
• Degree in Computer Science, IT, Data Science, AI, Engineering or related discipline, with relevant Azure AI, AWS ML, Google Cloud AI, NVIDIA, Databricks or equivalent certification.
• Analytical and strategic thinking with strong business acumen
• Strong AI, machine learning, generative AI, data platform and cloud architecture knowledge
• Strong stakeholder management, problem-solving and leadership
• Good communication, presentation and interpersonal skills
• Strong AI security, governance, privacy, risk and responsible-AI knowledge