AI Technical Architect

Technical Architect

Program Delivery & IP Engineering

The Role

We are looking for a Technical Architect who operates at the seam between client-facing delivery and internal IP development. You will partner directly with enterprise clients to define AI and data architecture — and then translate the hard-won patterns, decisions, and frameworks from those engagements into reusable assets that IG Labs owns and re-deploys.

This is not a pure consulting role and it is not a pure product role. It is the connector between them. You will be embedded in active engagements, you will shape architecture under real constraints, and you will be accountable for ensuring that what we build for one client becomes leverage for the next.

Key Responsibilities

Client Architecture Definition

• Partner with client stakeholders — CTO, VP Engineering, Chief Data Officers — to define AI and data platform architecture aligned to their strategic objectives
• Lead architecture discovery sessions: current-state assessment, gap analysis, future-state design, and roadmap sequencing
• Produce and own architectural artifacts: reference architectures, decision records (ADRs), data flow diagrams, integration blueprints, and governance frameworks
• Define and enforce non-functional requirements across security, scalability, observability, and regulatory compliance
• Serve as the technical authority on engagements — bridging business intent and engineering execution

IG Labs Collaboration & IP Derivation

• Work hand-in-hand with the IG Labs team to identify reuse opportunities within active client engagements
• Abstract generalizable patterns from bespoke client solutions — reference architectures, design templates, evaluation frameworks, and deployment playbooks — and contribute them to the IP library
• Participate in IP review cycles: peer review of contributed assets, validation of generalizability, and documentation of applicability conditions
• Actively drive toward Reuse Index targets — the primary delivery health metric tracking what proportion of each engagement is powered by pre-built IP
• Identify net-new IP opportunities from emerging client problems and partner with Labs to prototype and productize

Program Delivery

• Provide architectural oversight and technical governance across multiple concurrent client engagements
• Partner with delivery leads and project managers to ensure architectural decisions are reflected in project plans, sprint goals, and acceptance criteria
• Support pre-sales and solution design: contribute to SOWs, RFP responses, and technical proposals with defensible architectural thinking
• Mentor delivery engineers and junior architects; elevate technical craft across the team
• Flag architectural drift, scope risk, and technical debt in active engagements before they become delivery blockers

Qualifications

Required

Strongly Preferred

8+ years in technical architecture, solutions architecture, or principal engineering roles

Hands-on experience designing AI/ML, data platform, or cloud-native systems in production

Deep fluency in at least two major cloud platforms (AWS, Azure, GCP)

Experience working directly with senior client stakeholders to define architecture

Strong written and visual communication: architecture diagrams, decision records, executive summaries

Demonstrated ability to abstract reusable patterns from specific implementations

Comfortable operating with ambiguity in professional services or consulting environments

Experience with agentic AI systems, RAG architectures, LLM orchestration (LangChain, LlamaIndex, or similar)

Familiarity with MCP (Model Context Protocol) and its role in AI system integration

Background in regulated industries: financial services, healthcare, or insurance

Exposure to MLOps platform design, model governance, and AI lifecycle management

Prior experience in a professional services, systems integrator, or technology consulting firm

Track record of contributing to an IP library, accelerator repository, or internal knowledge base

Executive Certificate, Master’s, or equivalent advanced credentials

Core Competencies

Systems Thinking

Client Partnership

IP Mindset

Technical Authority

Pattern Recognition

Architectural Governance

Communication Clarity

Delivery Accountability