Technical Architect

Insight Global; Atlanta (GA); On-site; USD 150,000 - 210,000; Full time

Job summary

IG Labs, a unit of Insight Global, is seeking a Technical Architect to bridge client-facing delivery with internal IP engineering. You will shape AI/data platform architecture across engagements, translating patterns and decisions into reusable assets that IG Labs owns and redeploys.

You will lead architecture discovery, define governance, and ensure architecture decisions are reflected in project plans. The role requires deep expertise across cloud, AI, and agentic systems, with direct

Qualifications

• 8+ years in technical architecture, solutions architecture, or principal engineering roles.
• System design breadth and depth across cloud-native architectures and data modeling.
• Hands-on experience shipping production-grade agentic AI systems and RAG orchestration.
• Experience working directly with senior client stakeholders to define architecture.
• Strong written and visual communication: architecture diagrams and ADRs.
• Ability to abstract reusable patterns from client solutions and contribute to an IP library.

Responsibilities

• Define AI and data platform architecture with client stakeholders.
• Lead architecture discovery sessions: current‑state, gap analysis, future‑state design.
• Produce and own architectural artifacts: ADRs, data flow diagrams, blueprints, governance.
• Oversee non‑functional requirements: security, scalability, observability, compliance.
• Bridge business intent and engineering execution across engagements.
• Drive IP reuse by contributing assets to the IP library and reviewing contributions.
• Mentor delivery engineers and junior architects across multiple engagements.

Skills

System design

AI/ML fundamentals

Agentic AI / orchestration

Client stakeholder engagement

Executive communication

IP patterns

RAG architectures

MLOps concepts

Embedding spaces

Education

Master’s degree or equivalent

Executive Certificate

Tools

LangChain

LlamaIndex

Kubernetes

Cloud platforms (AWS/Azure/GCP)

Job description

IG LABS: Technical Architect: Program Delivery & IP Engineering

The RoleWe 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 making sure what we build for one client becomes leverage for the next.

The Technical Baseline: Three Pillars

The Technical Architect is evaluated against the same three pillars as our FDEs, at greater depth and breadth. You are the person who sets the technical bar, so you have to clear it convincingly in all three. Interviews probe each pillar directly.Pillar - What we evaluate, and what “deep” looks like

1. 1. System DesignFor the Technical Architect, system design is broad and deep. Everything expected of an FDE (databases, data modeling, strong programming) plus the architect's canvas: cloud architecture across at least two major providers, networking and connectivity, containerization and Kubernetes/orchestration, distributed systems and scalability, reliability and observability, and security and compliance as first-class design constraints. You reason about trade-offs across the whole system, not just one workstream.
2. 2. Traditional AI / MLA real understanding of how models actually work, not just how to call them. Neural network fundamentals across transformers, CNNs, and RNNs — attention, tokenization, training vs. inference, loss and evaluation, overfitting and regularization. Above all, a deep working understanding of embedding spaces: how text and other modalities become vectors, what distance and similarity mean, dimensionality, and how embeddings drive retrieval, clustering, and semantic matching.
3. 3. Applied AI / Agentic AI Very deep, hands-on experience building production-grade agentic systems. Not demos. Orchestration and control flow, tool and function calling, RAG and context engineering, memory and state, multi-step planning, evaluation and guardrails, cost and latency management, observability, and safe deployment into real environments. You have shipped agents that real users depend on, and you know why the hard ones fail.

The difference from the FDE bar is scope: an FDE goes deep on a workstream, the Architect reasons across the whole system and across concurrent engagements.

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, 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, elevating 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
• System design breadth and depth: cloud-native architecture across at least two major platforms (AWS, Azure, GCP), networking, containerization and Kubernetes, distributed systems, plus strong databases and data modeling
• Traditional AI/ML understanding: how transformers, CNNs, and RNNs work, and a deep working grasp of embedding spaces
• Hands-on experience designing and shipping production-grade agentic AI systems, not just prototypes
• 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
• Deep experience with RAG architectures, LLM orchestration (LangChain, LlamaIndex, or similar), and agent evaluation/observability
• Familiarity with MCP (Model Context Protocol) and its role in AI system integration
• MLOps platform design, model governance, and AI lifecycle management
• Experience with embedding/vector stores and retrieval design at enterprise scale
• Background in regulated industries: financial services, healthcare, or insurance
• 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 Communication
• Governance
• Delivery Accountability