Senior Solution Architect

Job Summary

Role Summary

The Generative AI Architect is responsible for defining, governing, and scaling enterprise‑grade GenAI solutions that are secure, compliant, cost‑effective, and aligned to measurable business outcomes.
This role sits at the intersection of AI engineering, enterprise architecture, cloud platforms, security, and transformation strategy, enabling the organization to move from GenAI experimentation to sustained production value.

Role Objective

To design and institutionalize GenAI platforms and solution patterns that:

• Accelerate business productivity and decision‑making
• Ensure compliance with regulatory, privacy, and Responsible AI standards
• Enable reuse, scale, and consistency across the enterprise
• Monetize GenAI capabilities across Run, Change, and Transform initiatives

Key Responsibilities

Key Responsibilities

1. Enterprise GenAI Architecture & Design

• Define end‑to‑end GenAI reference architectures, including:
• LLM selection (proprietary, open‑source, fine‑tuned)
• RAG (Retrieval Augmented Generation)
• Agent‑based and orchestration frameworks
• Establish build vs buy vs reuse architecture decisions
• Translate business use cases into scalable, production‑ready designs

2. Platform & Cloud Enablement

• Architect GenAI solutions on enterprise cloud platforms (Azure/AWS/GCP)
• Integrate GenAI with:
• Core business applications and APIs
• Data platforms, warehouses, and knowledge repositories
• Legacy and modernization programs
• Define standardized GenAI components for reuse across teams

3. Responsible AI, Security & Compliance

• Embed Responsible AI principles by design, including:
• PII/PHI protection
• Prompt safety and guardrails
• Transparency, auditability, and traceability
• Partner with Legal, Risk, Security, and Compliance teams to ensure:
• Regulatory adherence (e.g., GDPR, SOC2, ISO)
• Secure access, identity, and data handling
• Define governance frameworks for models, prompts, and data usage

4. Scalability, Performance & Cost Governance

• Architect for high availability, resilience, and scale
• Implement:
• Token and inference optimization strategies
• Model routing and caching
• Usage controls and quota management
• Drive AI cost governance (FinOps + MLOps alignment)

5. GenAI Engineering Standards & AI Ops

• Define LLMOps / MLOps standards for:
• CI/CD pipelines for models and prompts
• Model versioning and lifecycle management
• Monitoring hallucinations, drift, and performance
• Establish operational readiness for production GenAI workloads

6. Business Alignment & Value Realization

• Work with business and delivery leaders to:
• Prioritize high‑value GenAI use cases
• Define success metrics and ROI tracking
• Ensure GenAI initiatives deliver measurable outcomes, not just PoCs
• Support reuse across portfolios and business units

Key Stakeholders

• CIO / CTO / CDO
• Enterprise & Solution Architects
• Data Science & Engineering teams
• Security, Risk, Legal, Compliance
• Business and Transformation Leaders

Skill Requirements

Required Skills & Experience

Technical & Architectural

• 10–15+ years in enterprise architecture / solution architecture
• Hands‑on experience with:
• Large Language Models (LLMs)
• RAG, embeddings, vector databases
• API‑first and microservices architectures
• Strong cloud architecture experience (Azure preferred in enterprise contexts)
• Working knowledge of MLOps / LLMOps practices

Governance & Enterprise Design

• Experience designing for regulated environments
• Strong understanding of:
• Non‑functional requirements (security, scalability, compliance)
• Architecture standards and reference models

Business & Leadership

• Ability to translate business objectives into architecture decisions
• Experience influencing senior stakeholders (Director / VP / CXO)
• Strong communication and decision‑making skills

Other Requirements

Success Metrics

• Adoption rate of GenAI platforms and services
• Reduction in manual effort / cycle time
• Cost efficiency per transaction or inference
• Reuse of GenAI components across teams
• Zero critical security or compliance incidents

Role Positioning

This role is strategic and horizontal, typically part of:

• GenAI Center of Excellence (COE)
• Enterprise Architecture or Digital Platform teams
• Transformation programs focused on modernization and AI‑first delivery

Career Path (Indicative)

• Principal Architect – GenAI
• Enterprise AI Platform Lead
• Head of GenAI / AI COE
• Digital / Technology Transformation Leader