GCP Practice Architect II-AI​/ML

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. 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:
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), Big Query ML, AutoML, Generative AI capabilities (e.g., leveraging Gemini, RAG patterns), Document AI, and Contact Center AI. Incorporate modern GenAI orchestration frameworks (e.g., Lang Chain, Llama Index) and vector databases (e.g., Vertex AI Vector Search, Alloy

DB 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, Big Query, 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 Fin Ops 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…