Enterprise AI Architect

algoleap; Bengaluru; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

algoleap is seeking a seasoned Enterprise AI Architect in Bengaluru, in hybrid mode (3 days in office) to shape AI strategy and architecture communication. You will craft ADRs, capability models, and platform narratives, working with senior leadership to prepare leadership briefings and client collateral.

The role requires 15 years in IT with enterprise architecture and AI program experience, and exceptional written communication to translate executive intent into polished artifacts for internal

Qualifications

• 15 years of IT experience with enterprise/solution architecture or technology strategy roles.
• Proven AI/ML/GenAI program experience including platform architecture and LLM integration.
• Proven track record producing executive-grade written artifacts and C-suite materials.
• Strong command of enterprise architecture frameworks (TOGAF or equivalent).
• Exceptional written communication and client-ready document design.
• Advanced proficiency with PowerPoint and ability to produce polished decks.
• Experience translating executive intent into artifacts with minimal iterations.

Responsibilities

• Translate AI strategy decisions into durable written artifacts: ADRs, capability frameworks, reference architectures, platform narratives, and blueprints.
• Maintain AI architecture repository with decisions, rationale, and dependencies.
• Create strategy decks and socialization materials for engineering, leadership, and clients.
• Support senior leadership in stakeholder presentations, leadership briefings, and client collateral.
• Convert complex technical concepts into clear, decision-oriented narratives.
• Provide guardrails and framework inputs to delivery teams for AI programs.

Skills

Enterprise architecture

AI/ML / GenAI

Executive communication

Technical writing

PowerPoint

Stakeholder management

Education

TOGAF certification

Azure Solutions Architect certification

Tools

Azure OpenAI

AWS Bedrock

GCP Vertex AI

Job description

Experience: 15 years

Location: Bengaluru — Embassy Golf Links (EGL) area | Hybrid, 3 days/week in office

We are seeking a seasoned Enterprise AI Architect to serve as the intellectual engine behind our AI strategy and architecture communication function. This role translates approved AI strategy decisions into high-quality written and visual artifacts — architecture decision records (ADRs), capability frameworks, platform narratives, strategy decks, and socialization materials — for both internal leadership and external client audiences.

The role works closely with senior leadership (directly supporting Amit) in producing content for stakeholder presentations, leadership briefings, and client-facing collateral. The ideal candidate combines deep enterprise architecture credibility with exceptional structured-writing and executive-communication skills.

Key Responsibilities

AI Vision, Strategy & Architecture Documentation

• Translate approved AI strategy decisions into durable written artifacts: Architecture Decision Records (ADRs), AI capability frameworks, reference architectures, platform narratives, and target-state blueprints.
• Develop and maintain the AI architecture repository — ensuring decisions, rationale, trade-offs, and dependencies are captured with rigor and traceability.
• Author strategy decks and socialization materials tailored to distinct audiences: engineering teams, business unit leadership, executive committees, and external clients.

Executive & Stakeholder Content Support

• Support senior leadership (Amit) in producing content for stakeholder presentations, leadership briefings, board-level updates, and client-facing collateral.
• Convert complex technical concepts (agentic architectures, LLM platform design, data governance, security postures) into crisp, decision-oriented narratives.
• Ensure consistency of messaging, terminology, and visual identity across all strategy and architecture artifacts.

Architecture Advisory

• Participate in AI strategy and architecture review forums; capture decisions and articulate their downstream architectural implications.
• Evaluate emerging AI platforms, patterns, and vendor capabilities; produce point-of-view (PoV) papers and comparative assessments.
• Provide architectural guardrails and framework inputs to delivery teams executing AI programs (POCs, pilots, production rollouts).

Required Qualifications & Experience

• 15 years of overall IT experience, with significant time in enterprise architecture, solution architecture, or technology strategy roles.
• Demonstrated experience in AI/ML or GenAI programs — platform architecture, LLM integration, cloud AI services (Azure OpenAI, AWS Bedrock, GCP Vertex, or equivalent).
• Proven track record producing executive-grade written artifacts: ADRs, capability models, reference architectures, strategy documents, and C-suite presentations.
• Strong command of enterprise architecture frameworks (TOGAF or equivalent) and modern cloud-native architecture patterns.
• Exceptional written communication — able to write with precision, structure, and audience awareness.
• Advanced proficiency with PowerPoint and document design; ability to independently produce polished, client-ready decks.
• Experience working directly with senior executives and translating their intent into finished artifacts with minimal iteration.

Preferred Qualifications

• Consulting or advisory background with enterprise clients (financial services exposure a plus).
• Familiarity with AI governance, responsible AI frameworks, data residency, and enterprise security requirements (Entra ID, in-tenant deployment models, zero data egress patterns).
• Exposure to agentic AI frameworks (LangGraph, Google ADK, Copilot Studio, or similar).
• TOGAF, Azure Solutions Architect, or comparable certifications.

Success Measures (First 6–12 Months)

• A fully operational ADR and architecture documentation practice with consistent templates and cadence.
• Leadership and client-facing decks produced on time, requiring minimal senior rework.
• Positive stakeholder feedback on clarity and decision-usefulness of strategy artifacts.