Practice Architect II – AI/ML

TEKsystems

. Own architecture direction for agentic AI and full-stack solutions across assigned engagements .

Posted 11/3/2026full-timeRemote • United StatesSeniorLead💰 $156,000 - $234,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecture direction for agentic AI and full-stack solutions, with a strong focus on scalable solution architectures and production delivery across cloud platforms. Proven ability to mentor engineering teams, drive alignment among stakeholders, and manage technical trade-offs effectively.

Highest-signal resume keywords

Architecture Direction for Agentic AIProduction AI/Agentic Systems DevelopmentCloud Platform Delivery (AWS, Azure, GCP)Enterprise Data Onboarding and GovernanceMentoring and Leading Distributed Engineering Teams

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Solution ArchitectureSoftware DevelopmentAI-Assisted CodingCode ReviewsSQLPythonTypeScript/NodeKnowledge FabricRAG and Retrieval ArchitectureAgent Security

Soft Skills

Technical CommunicationStakeholder AlignmentMentoring

Tools & Technologies

MCPContainersCI/CDIaCLangGraphLlamaIndex

Industry Keywords

Agentic AIEnterprise Data GovernanceSemantic ModelingCloud-Agnostic DeliveryEngineering Standards

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformNode.jsPythonSQLTypeScript

About the role

Key responsibilities & impact

Own architecture direction for agentic AI and full-stack solutions across assigned engagements
Translate business and technical requirements into scalable, sustainable solution architectures
Set architecture standards and design patterns for delivery teams
Own code review and architecture review gates and make final calls on technical trade-offs
Write production code for customer engagements approximately 40–60% of the time
Build and own reusable accelerators, frameworks, and reference architectures
Evaluate emerging technologies and architecture patterns and decide what enters the stack
Unblock engineering teams on implementation problems
Provide technical direction to engineering pods across concurrent engagements
Lead offshore technical leads and ensure design intent survives handoff to distributed teams
Mentor engineers on architecture, code quality, and modern engineering practices
Serve as senior technical voice to customer architects, engineering leaders, and executives
Explain architecture decisions, risks, and trade-offs to technical and non-technical audiences
Surface technical risks and dependencies early with mitigation options
Drive alignment across customer product, engineering, and business stakeholders
Deliver working systems in production from enterprise data onboarding through operation
Build collaboration across global and offshore teams and leave behind extensible implementations

Requirements

What you’ll need

Bachelor's degree in Computer Science, Engineering, Information Technology, or a related discipline
10+ years in software engineering and architecture, including 3+ years as a lead or principal architect
2+ years building production AI/agentic systems deployed and operating, not pilots or proofs of concept
Experience onboarding enterprise data and building a governed knowledge or semantic layer, including entitlement and lineage
Ability to describe the security and identity model for agents acting on enterprise data
Currently coding and able to complete a hands-on technical assessment
Experience leading offshore or distributed engineering teams
Experience defining RACI across customer, onshore, and offshore teams on a live engagement
Production delivery on at least two of AWS, Azure, or GCP
Customer-facing experience at engineering-leadership and executive level
Agentic AI, AI-powered solution design, and modern application architecture
Solution architecture and system design
Hands-on software development and prototyping
AI-assisted coding at scale for production deployment
Code reviews, engineering standards, and quality governance
Enterprise data onboarding, including source access, ownership, entitlement, classification, and quality gating
Knowledge fabric, semantic modeling, entity resolution, lineage, and freshness
RAG and retrieval architecture, including vector and hybrid search, embedding pipelines, retrieval quality tuning, context, and memory management
Agent security, including agent identity, least-privilege tool access, data-boundary enforcement, and audit
Agent execution harnesses, including tool and component boundaries, orchestration, failure handling, and human-in-the-loop
Evaluation harnesses, regression suites, groundedness and retrieval quality metrics, and cost and latency instrumentation
Cloud-agnostic delivery across AWS, Azure, and GCP
Python and TypeScript/Node
Strong SQL
Agent frameworks such as LangGraph, LlamaIndex, or equivalent
MCP, containers, CI/CD, and IaC

Benefits

Comp & perks

Additional earnings may be available through annual bonuses
Profit sharing
Medical, Dental, and Vision
Critical Illness, Accident, and Hospital coverage
401(k) Retirement Plan with pre-tax and Roth post-tax contributions
Voluntary Life and AD&D insurance for employee and dependents
Short- and Long-Term Disability
Health Spending Account (HSA)
Transportation Benefits
Employee Assistance Program
Time Off/Leave (PTO, Vacation or Sick Leave)
Fully remote position