Enterprise Architect

About the role

Proven experience driving AI strategy and implementation across multiple functions is required. The ideal candidate will have the ability to engage CXO/VP-level stakeholders and influence decision-making, as well as strong program management skills to oversee AI roadmap, execution, and governance.

Responsibilities

• AI Strategy, Advisory & Opportunity Identification: Engage with client stakeholders to understand business challenges and identify AI/GenAI opportunities, shape AI strategy, use cases, and roadmap aligned to client objectives and deal strategy, and provide advisory on AI adoption, readiness, and transformation approach
• Solution Architecture & Presales Solutioning: Design enterprise-grade AI/GenAI solution architectures tailored to client needs, define integration patterns with existing enterprise ecosystems, select appropriate AI platforms, tools, and accelerators aligned to solution requirements, and collaborate with CoEs, domain teams, and account teams to build comprehensive solution offerings
• POC Development & Deal Acceleration: Develop rapid PoCs, prototypes, and demonstrations to validate AI solution feasibility, showcase business value through working demos, use-case walkthroughs, and client presentations, support RFP responses, solution bids, and technical discussions during deal cycles, and accelerate deal closure by de-risking solution approaches through demonstrable outcomes
• AI Enablement & Handover to Account Teams: Create reusable solution blueprints, architecture documents, and implementation guidelines, ensure structured knowledge transfer of AI solutions, POCs, and architecture to account/delivery teams, support accounts during transition from presales to delivery by clarifying solution intent and design decisions, and enable continuity by ensuring accounts are equipped to implement and scale the solution
• Collaboration & Ecosystem Engagement: Work closely with account teams, delivery units, AI CoEs, and domain SMEs, orchestrate contributions across multiple teams to build end-to-end AI solutions, and facilitate alignment between business, engineering, and architecture stakeholders
• Innovation, Reusability & Thought Leadership: Stay updated with evolving AI/GenAI technologies and assess applicability, build reusable accelerators, frameworks, and solution assets, conduct workshops, client demos, and knowledge-sharing sessions
• AI Lifecycle Guidance (Advisory): Guide teams on AI lifecycle best practices, recommend MLOps / LLMOps approaches for scalable execution, advise on performance, cost optimization, and scalability considerations
• Responsible AI, Risk & Compliance Advisory: Provide guidance on Responsible AI principles, security, and compliance considerations, identify risks and recommend mitigation approaches
• Vendor & Platform Advisory: Evaluate AI platforms, tools, and partner ecosystems for suitability, recommend build vs buy decisions aligned to client context

Requirements

• Expertise in end-to-end AI lifecycle, understanding of ethical AI, regulatory compliance, data privacy norms
• Experience in setting up AI Centers of Excellence (CoE), certifications in AI/ML, cloud, or enterprise architecture
• Strong knowledge of technologies such as Generative AI, AI/ML Architecture & Solution Design, Python ecosystem, Cloud AI platforms, Data Engineering & Vector Databases
• Expertise in MLOps / LLMOps / GenAI Ops, production-grade enterprise implementations, enterprise data architecture, and integrating AI solutions into enterprise ecosystems
• Strong awareness of AI security, Responsible AI principles, and bias mitigation

Qualifications

A Bachelor’s degree in information technology, Business or related field is required. An MBA is also preferred. The ideal candidate will have experience in AI/GenAI Solution Architecture, Enterprise AI Strategy & Governance, Python & AI/ML Frameworks, and Cloud AI Platforms, with 5+ years of experience in AI/ML/GenAI.

Pay

The salary range for this position is $151,500 - $204,900 per year.