Enterprise Architect – Legacy Platform Modernization (AIEnabled)

Who are we looking for?

15+ years of relevant IT experience, including Enterprise Architecture will define and govern the futurestate architecture for a large, custombuilt legacy enterprise platform (C/C++, Oracle, WIN32) undergoing modernization. The role focuses on architectural strategy, nonfunctional requirements, AIenabled transformation, and technology risk mitigation while preserving critical platform performance characteristics.

Key Responsibilities

• Define the futurestate enterprise architecture across application, data, integration, infrastructure, and AI/ML enablement layers.
• Establish modernization strategies and architectural patterns (replatform, refactor, hybrid) aligned to scalability, resiliency, and cost efficiency.
• Preserve and evolve critical NFRs (performance, throughput, availability, compute efficiency) during legacy transformation.
• Define AI/ML integration patterns, including model lifecycle, data pipelines, inference services, and governance for analytics, automation, and decision support.
• Identify opportunities to leverage AI/ML for risk reduction, performance optimization, observability, and intelligent automation.
• Define integration and interoperability standards, including APIled, eventdriven, and datacentric architectures.
• Identify and mitigate technology, operational, obsolescence, and modelrisk associated with legacy platforms and AI adoption.
• Govern architecture decisions through principles, standards, and guardrails, ensuring consistency across delivery teams.
• Collaborate with engineering, data, security, and operations teams to ensure alignment with enterprise controls and policies.

Required Skills & Experience

• Proven experience as an Enterprise or Solution Architect on largescale legacy modernization programs.
• Strong architectural background in C/C++, Oracle databases, monolithic or clientserver platforms, and distributed systems.
• Experience defining targetstate architectures and transition roadmaps.
• Strong understanding of AI/ML architecture concepts (data pipelines, model deployment, inference patterns, governance).
• Deep expertise in nonfunctional architecture (performance engineering, scalability, resiliency, capacity planning).
• Experience with modern integration patterns, APIs, messaging, and data pipelines.
• Ability to operate at enterprise and executive level, translating complexity into clear architectural direction.

Nice to Have (Not Mandatory)

• Exposure to capital markets, trading, or risk platforms.
• Experience applying AI/ML in highperformance or regulated enterprise systems.

Stakeholder Management

• Act as the primary point of contact between business and technology teams.
• Conduct workshops, training sessions, and status updates.
• Manage priorities, expectations, and project timelines.

Business Skills

• Strong analytical and problem-solving abilities.
• Ability to break down complex derivative workflows.
• Clear documentation and communication skills.