As an Enterprise AI Architect, you will lead the evolution of Application Development (AD) and Application Maintenance Services (AMS) from AI-assisted work to governed, agent-enabled operations. You will own the single shared foundation of enterprise knowledge, AI harnesses, agents, Model Context Protocol (MCP) integrations, and governance that powers both the AD loop and the AMS loop.

This role is responsible for defining and driving the maturity roadmap that moves both AD and AMS from harness-driven delivery to enterprise-scaled autonomy. We are looking for a seasoned architect with deep enterprise architecture experience and a proven record of leading production-grade AI, data, and automation initiatives across engineering, operations, security, and risk teams.

Your Role Responsibilities and Duties

• Strategy & Maturity Roadmap: Define the AD/AMS AI strategy, set entry and exit criteria for each maturity level, and segment use cases by value, risk, and readiness.
• Shared AI Foundation: Own the reference architecture and the Enterprise Knowledge Base (code, JIRA, ServiceNow, runbooks, and logs), with governed RAG, permissions, and lineage.
• Harness & Agent Architecture: Set enterprise standards for approved harnesses, prompts, skills, sub-agents, and multi-agent patterns, and define clear boundaries between assisted and autonomous work.
• MCP & Enterprise Integration: Establish the MCP registry, tool certification process, and action categories ranging from read-only to approval-required.
• Closed-Loop Engineering & Operations: Connect tests, reviews, pipelines, telemetry, and incidents to agent workflows so that AD and AMS continuously learn from each other.
• Governance & Responsible AI: Define risk classification, human-in-the-loop checkpoints, kill switches, rollback, and audit requirements, ensuring autonomy is earned, not assumed.

Required Skills and Qualifications

• 15+ years of experience in technology, engineering, architecture, or transformation roles, including 8+ years in enterprise architecture, engineering platforms, cloud transformation, or large-scale delivery transformation.
• Proven leadership of production-grade AI, data, automation, or intelligent-platform initiatives.
• Experience leading cross-functional programs across engineering, operations, security, data, and risk teams.
• Enterprise architecture expertise across application, data, integration, security, cloud, and operating-model domains.
• Strong grounding in LLMs, retrieval-augmented generation (RAG), embeddings, tool calling, and multi-agent orchestration.
• Knowledge of AI harnesses (Claude Code, GitHub Copilot, Gemini, Devin) and agent frameworks (LangGraph, ADK, Semantic Kernel).
• Solid foundations in software engineering, DevSecOps, CI/CD, observability, and SRE.
• Ability to brief executive and technical audiences on complex AI and architecture decisions.

Preferred Qualifications

• Bachelor’s or master’s degree in Computer Science, Engineering, or a related field; relevant cloud, security, SRE, or AI certification.
• Experience with GCP Vertex AI / Gemini; familiarity with Azure AI or AWS Bedrock is a plus.
• Experience in telecom, financial services, or another large-scale regulated environment.

Mandatory Skills

Enterprise Architecture, LLMs & RAG, Multi-Agent Orchestration, AI Harnesses (Claude Code / GitHub Copilot), MCP, DevSecOps & CI/CD, AI Governance.

What We Offer

• Bootstrapped and financially stable with high pre-money valuation.
• Above-industry remuneration.
• Additional compensation tied to renewals and pilot project execution.
• Additional lucrative business development compensation.
• Chance to work closely with industry experts driving strategy with data and analytics.
• Firm-building opportunities that provide a platform for holistic professional development, growth, and branding.
• An empathetic, excellence-driven, and results-focused organization that believes in mentoring and growing a team with a constant emphasis on learning.