Practice Lead Architect

TEKsystems•Dallas, TX

3d•$160,000 - $225,000•Remote

About The Position

Practice Lead Architect (Full-time/Remote) Think of TEKsystems Global Services (TGS) as the growth solution for enterprises today. We unleash growth through technology, strategy, design, execution and operations with a customer-first mindset for bold business leaders. We deliver cloud, data and customer experience solutions. Our partnerships with leading cloud, design and business intelligence platforms fuel our expertise. We value deep relationships, dedication to serving others and inclusion. We drive positive outcomes for our people and our business, and we stay true to our commitments and act in harmony with our words. We exist to create significant opportunity for people to achieve fulfillment through career success. Ready to join us? Here’s what the opportunity supported through our TGS Talent Acquisition Team requires: We are hiring a Practice Leader / Principal responsible for building and scaling our GCP- and AWS-aligned Cloud Operations practice across North America and EMEA. This role owns the GTM relationships with both Google Cloud and AWS, drives new logo acquisition through co-sell motions, and — critically — leads the operationalization of TGS's Pillar 4 Accountability Moats capability across all CSP services under management. You are the senior-most multi-cloud voice within TGS Cloud Operations: technical enough to command respect from Google and AWS engineering teams, commercial enough to lead joint pursuits, and principled enough to institutionalize Responsible AI governance and AI FinOps accountability at scale. You will ensure that every AI service TGS manages, integrates, or operates on behalf of a client carries audit-grade governance, cost accountability, and indemnification — regardless of which CSP provides the underlying capability.

Requirements

15+ years of progressive experience in cloud consulting, managed services, or professional services; at least 7 years in senior practice leadership roles.
Deep technical proficiency in Google Cloud and AWS — demonstrated through direct architecture or delivery leadership on enterprise programs spanning AI/ML, data platforms, or managed cloud operations.
Demonstrated experience designing or operating AI governance frameworks: model risk management, Responsible AI controls, NIST AI RMF, EU AI Act compliance, or equivalent.
Working knowledge of AI FinOps: unit economics for AI/ML workloads, GPU/TPU cost allocation, model inference cost optimization, and chargeback frameworks for AI spend.
Track record of building a technology practice from inception or early stage to material scale — including service-line design, GTM, hiring, and commercial ownership.
Big 5 / Tier-1 consulting or professional services pedigree (Accenture, Deloitte, IBM Consulting, Capgemini, PwC, EY, Infosys, TCS, Wipro, HCL, Cognizant, or equivalent).
Strong presales track record with demonstrable history of closed-won pursuits at meaningful TCV, with personal leadership of orals, solution defense, and commercial close.
Extensive experience building and operating global delivery teams across multiple geographies, including India and at least one EMEA hub; comfortable running a follow-the-sun model.
Demonstrated experience designing and operating cloud-native Day 2 operations for enterprise GCP environments — including steady-state managed services, SRE-led operations, incident and problem management, and operational governance across GKE, serverless, and data platform workloads.
Hands-on familiarity with GCP operational tooling — Google Cloud Operations Suite, Security Command Center, Cloud Armor, GKE operations, and integration with enterprise ITSM platforms (ServiceNow, PagerDuty, or equivalent).
Established senior relationships within Google Cloud and AWS partner and field organizations in North America and EMEA.
Proven new logo acquisition profile — this role is focused on building pipeline and winning new clients, not farming existing accounts.
Cloud
Architecture
Cloud Operations
RFP Program Experience

Nice To Haves

Active Google Cloud certifications: Professional Cloud Architect, Professional Cloud DevOps Engineer, Professional Cloud Security Engineer, or Professional Machine Learning Engineer.
Active AWS certifications: Solutions Architect Professional, DevOps Engineer Professional, Machine Learning Specialty, or Security Specialty.
Prior experience within Google Cloud (PSO, CE, Partner org) or AWS (ProServe, SA, or Partner org), or at a top-tier Premier Partner for either hyperscaler.
Hands-on familiarity with AI governance tooling: Vertex AI Model Monitoring, AWS SageMaker Clarify/Model Monitor, MLflow, WhyLabs, Arize AI, or equivalent.
Hands-on familiarity with FinOps tooling for AI: CloudZero, Apptio Cloudability, AWS Cost Explorer with ML tagging, GCP Billing export + BigQuery analytics, or equivalent.
Experience structuring or negotiating contractual indemnification provisions for managed services, AI outputs, or technology service delivery.
Working knowledge of enterprise observability and AIOps: Dynatrace, Datadog, New Relic, Splunk, OpenTelemetry.
Exposure to regulated industries — Financial Services, Healthcare, Public Sector — and associated compliance frameworks (DORA, HIPAA, HITRUST, FedRAMP, EU AI Act, NIST AI RMF).
Bachelor's degree in Computer Science, Engineering, or related discipline; MBA or advanced degree a plus.

Responsibilities

Define and execute the multi-year strategy for GCP and AWS Cloud Operations across NA and EMEA, including service lines, solution offers, target segments, and commercial model.
Build the practice's solutions catalog: service packs, reference architectures, delivery playbooks, SLAs, and pricing frameworks aligned to Google Cloud AI (Gemini, Vertex AI), AWS AI/ML (SageMaker, Bedrock, Q), security, and sovereign cloud priorities.
Define and operationalize GCP Cloud-Native Day 2 Operations as a core service line within the practice portfolio — spanning the full steady-state lifecycle from go-live through continuous operations, including incident and problem management, change and release management, capacity planning, patching and vulnerability remediation, configuration drift detection, and cloud-native SRE practices across GKE, Cloud Run, and serverless workloads.
Embed Pillar 4 accountability structures — AI FinOps, Responsible AI as a Service, and indemnified AI governance — as standard components of every service pack and SOW, not optional add-ons.
Establish the practice operating rhythm: pipeline reviews, capability roadmap, hiring plan, partner-program compliance, and capacity planning across both hyperscaler programs.
Own TGS's position in Google Cloud Partner Advantage and AWS Partner Network (APN), including progression of specializations, expertise designations, and MSP qualification.
AI FinOps: Design and operate cost governance frameworks for all AI/ML workloads under management — covering GCP (Vertex AI, BigQuery ML, Cloud TPUs) and AWS (SageMaker, Bedrock, EC2 inferencing). Deliver real-time unit economics, allocation, chargeback, and optimization against client AI spend.
Responsible AI as a Service: Institutionalize fairness, explainability, bias detection, model drift monitoring, and data lineage controls across every AI/ML service TGS manages. Deliver governance reports, risk registers, and attestations that satisfy board-level and regulatory scrutiny (DORA, NIST AI RMF, EU AI Act, HIPAA).
Indemnified AI for CSP Services: Lead the development of TGS's indemnification framework for AI outputs — covering model hallucinations, bias-driven decisions, and data residency violations in managed AI pipelines. Work with TGS Legal to define contractual coverage and with clients to embed indemnification into MSA schedules.
Workforce Transition Governance: Build the accountability layer for AI-driven workforce change within client organizations — ensuring TGS-managed AI implementations include impact assessments, retraining commitments, and governance trails that satisfy HR, union, and regulatory stakeholders.
Audit-Grade Governance Infrastructure: Develop the logging, attestation, policy-as-code, and audit trail frameworks that allow clients to produce evidence-ready AI compliance packages for internal audit, external regulators, and cyber insurers.
Develop and maintain senior relationships across Google Cloud Partner, Sales, Customer Engineering, PSO, and Industry teams; and across AWS Partner Organization, Sales, Solutions Architecture, and Marketplace teams in NA and EMEA.
Align the practice to Google Cloud strategic priorities (AI, Data Cloud, Security Operations, GKE) and AWS strategic priorities (Bedrock, SageMaker, Control Tower, GuardDuty) — ensuring TGS is positioned on every relevant co-sell opportunity.
Embed in both hyperscalers' field cadences through joint account planning, QBRs, solution councils, and industry huddles.
Co-develop joint solution offers and enablement materials that help Google and AWS field teams position TGS's accountability-first Cloud Operations model with confidence.
Drive co-sell pipeline through Google Cloud Marketplace, AWS Marketplace, Partner Advantage, and APN funding programs.
Lead the presales and pursuit engine for GCP and AWS new logos across NA and EMEA — qualify, shape, and close strategic engagements with strong attachment to managed cloud operations and AI governance.
Personally lead priority pursuits as the technical, commercial, and governance deal lead — including oral defenses, solutioning workshops, executive meetings, and commercial negotiations.
Build the presales operating model: RFP response playbooks, solutioning pods, estimating models, competitive positioning for AI governance differentiation, and win/loss discipline.
Position TGS's indemnified AI and Responsible AI-as-a-Service capabilities as hard-to-replicate moats in competitive RFPs against hyperscaler PSO, SIs, and boutique AI firms.
Design and scale the global delivery footprint across India, Budapest, and North America — assembling the right mix of architects, SREs, AI/ML engineers, FinOps analysts, and governance specialists.
Own the design, standards, and delivery of GCP Cloud-Native Day 2 Operations across client engagements — establishing practice-wide runbooks, operating procedures, and SLA frameworks for steady-state cloud operations covering Google Cloud Operations Suite (Cloud Monitoring, Cloud Logging, Cloud Trace), Security Command Center, GKE cluster operations, Apigee API management, and multi-region availability management.
Drive continuous improvement across Day 2 operations through AIOps-led event correlation, automated remediation, and proactive capacity and performance management — reducing mean time to detect (MTTD) and mean time to resolve (MTTR) as measurable client outcomes.
Establish observability standards across all GCP-managed estates — integrating Google Cloud Operations Suite with third-party tooling (Dynatrace, Datadog, Splunk, OpenTelemetry) to deliver unified monitoring, alerting, and incident response across hybrid and multi-cloud environments.
Ensure delivery excellence on every engagement: measurable outcomes, transparent AI cost and risk reporting, and continuous improvement against availability, resiliency, cost, and governance metrics.
Institutionalize delivery assets — runbooks, AI governance playbooks, FinOps dashboards, automation, and a knowledge base that improves the practice's economics and quality over time.
Partner with peer practice leaders (AWS, Azure, Data, Security) to share capacity, cross-skill talent, and embed Responsible AI governance consistently across all TGS delivery tracks.
Represent TGS Cloud Operations in the Google Cloud and AWS ecosystems — Google Cloud Next, AWS re:Invent, partner summits, analyst briefings (Gartner, Forrester, ISG), and customer advisory forums.
Publish a distinct TGS point of view on AI governance, FinOps for AI, and indemnified AI services — establishing TGS as a recognized authority on Responsible AI in managed services contexts.
Develop the talent pipeline through Google and AWS certification programs, Responsible AI training, FinOps practitioner programs, and targeted leadership development.