[Hiring] GCP Practice Architect II-AI/ML @TEKsystems

Role Description

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.

Architecture & Delivery Excellence:

• Lead the technical design and architecture of complex, end-to-end AI/ML solutions on Google Cloud Platform, leveraging a comprehensive suite of services including Vertex AI (Pipelines, Training, Prediction, Feature Store), BigQuery ML, AutoML, Generative AI capabilities (e.g., leveraging Gemini, RAG patterns), Document AI, and Contact Center AI.
• Incorporate modern GenAI orchestration frameworks (e.g., LangChain, LlamaIndex) and vector databases (e.g., Vertex AI Vector Search, AlloyDB with pgvector).
• Develop and implement robust, scalable, and production-grade AI/ML systems, ensuring they meet stringent performance, security, and reliability requirements for enterprise clients.
• Ensure infrastructure is deployed securely using Infrastructure as Code (IaC) standards like Terraform, enforcing GCP security best practices (VPC Service Controls, IAM, CMEK).
• Architect and implement comprehensive MLOps and LLMOps frameworks on GCP for efficient model development, deployment, monitoring, and lifecycle management, including CI/CD pipelines, model versioning, and automated retraining strategies.
• Design and oversee the implementation of data engineering pipelines on GCP for AI/ML use cases, covering data ingestion, preprocessing, feature engineering, and data governance using services like Google Cloud Storage, BigQuery, Dataflow, and Pub/Sub.
• Embed Responsible AI and AI Governance into architectures, utilizing tools like Vertex Explainable AI and implementing data privacy guardrails to mitigate risks of model bias, toxicity, and hallucinations.

Project Leadership & Delivery Management:

• Lead the technical delivery of significant GCP AI/ML projects, ensuring adherence to architectural best practices, project scope, timelines, and budget constraints.
• Provide technical leadership and guidance to cross-functional project teams, including AI/ML engineers, data scientists, and data engineers, fostering a collaborative and high-quality delivery environment.
• Manage technical risks and issues throughout the project lifecycle, facilitating timely resolution and communicating effectively with stakeholders.
• Ensure financial and contractual responsibility for the profitability of assigned AI/ML engagements.
• Apply Cloud FinOps principles to AI workloads, right-sizing compute (GPUs/TPUs) and optimizing token usage to manage enterprise cloud spend.
• Conduct deep-dive "hands-on" education/training sessions to transfer knowledge to customers considering, or already using GCP.

Client Engagement & Technical Advisory:

• Collaborate closely with client stakeholders to understand their business objectives, technical requirements, and challenges, translating them into effective GCP AI/ML solution architectures.
• Lead Value Engineering efforts to help clients articulate the ROI of AI/ML initiatives, ensuring clear KPIs are established to move projects successfully from Proof of Concept (PoC) into enterprise production.
• Present and articulate complex technical solutions, architectural designs, and project progress to both technical and non-technical client audiences, building trust and ensuring alignment.
• Act as a key technical point of contact for clients during project execution, addressing concerns and managing expectations.
• Support pre-sales activities by contributing to solution design, proposal development, technical presentations, and proof-of-concept (PoC) demonstrations for GCP AI/ML opportunities.
• Plan, facilitate, and lead strategic workshops, hackathons, and ideation sessions for customers within the Google ecosystem, leveraging partner-led discovery frameworks to drive GenAI and ML adoption.

Practice Development & Mentorship:

• Contribute significantly to the development and refinement of TEKsystems' GCP AI/ML practice by creating reusable intellectual property (IP), best practices, reference architectures, and delivery methodologies.
• Mentor and guide junior architects and AI/ML engineers, fostering their technical and professional growth within the practice.
• Stay current with the latest advancements in GCP AI/ML services, open-source frameworks, and industry trends, sharing knowledge and driving innovation within the team.
• Participate in architectural discussions to build confidence and ensure customer success when building new and migrating existing applications, software, and services on the GCP platform.

Qualifications

• Bachelor’s/master’s degree in computer science, Engineering, Data Science, Artificial Intelligence, Mathematics, or a related technical field, or equivalent, relevant experience.
• A minimum of 12+ years of progressive experience in Information Technology, with a strong emphasis on AI/ML, data analytics, and cloud computing.
• At least 5-7+ years of direct, hands-on experience in designing, developing, and implementing enterprise-grade AI/ML solutions, with substantial project experience on Google Cloud Platform.
• A minimum of 2-3+ years of experience in a technical leadership role, guiding project teams or significant workstreams in the delivery of AI/ML solutions.
• Demonstrated experience with the complete lifecycle of AI/ML projects on GCP, from initial requirements gathering and PoC development through to production deployment, monitoring, and optimization.
• Proven experience in architecting and implementing MLOps systems in enterprise environments, including building, scaling, and optimizing machine learning systems on GCP.
• Strong client-facing experience, including presenting technical solutions, participating in workshops, and effectively communicating with diverse stakeholders.
• Experience in developing data and AI solutions utilizing Google Cloud Data services, and architecting System Design for Data & AI Modernization efforts.
• At least 1 year of experience in Generative AI using Hyperscalers, employing techniques such as RAG, prompt engineering, and fine-tuning custom models from a marketplace.
• Active Google Cloud Professional Certification is highly preferred (Professional Machine Learning Engineer and/or Professional Cloud Architect).

Requirements

• Architecture
• Cloud
• Google Cloud
• Design
• Solution architecture
• Development
• Enterprise architecture
• Professional services
• Artificial intelligence
• Machine learning
• Agile
• AWS
• Azure
• Java
• Automation
• DevOps
• Data
• Project management
• Communication and leadership skills
• Terraform/IaC
• LangChain/GenAI Orchestration
• FinOps
• Responsible AI
• Value Engineering

Benefits

• Medical, Dental, and Vision
• Critical Illness, Accident, and Hospital
• 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available
• Life Insurance (Voluntary Life and AD&D 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)

Job Title

Practice Architect II- GCP AI/ML

Job Type & Location

This is a Permanent position based out of Baltimore, MD.

Pay and Benefits

The pay range for this position is $156,000.00 - $234,000.00/yr. Additional earnings may be available through incentive programs like annual bonuses, profit sharing, etc.

Workplace Type

This is a fully remote position.

Application Deadline

This position is anticipated to close on Jun 15, 2026.