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# GCP Practice Architect II-AI/ML

- **Company:** TEKSYSTEMS INC.
- **Location:** Linthicum Heights, MD, United States (Remote available)
- **Salary:** $156,000.0 - $234,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Agile Methodology, Artificial Intelligence, Amazon Web Services, Application Frameworks, Microsoft Azure, BigQuery, Cloud Computing, Cloud Storage, Data as a Services, Information Engineering, Data Governance, Data Transformation, DevOps, Data Flow Control, Identity and Access Management, Machine Learning, Azure Machine Learning, Search Technologies, Software Deployment, Value Engineering, Graphics Processing Unit (GPU), Google Cloud, Feature Engineering, Data Ingestion, Prompt Engineering, Generative AI, Infrastructure as Code (IaC), Amazon Virtual Private Cloud (VPC), Kubernetes, Information Technology, Data Analytics, Machine Learning Operations, Terraform, Software Version Control
- **Published:** May 19, 2026
- **Apply:** https://www.juju.com/job/00000000g0ziax

## About the Role

3 to over 10 members. · 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. Enterprise Req Skills 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. Job Title Practice Architect II- GCP AI/ML Top Skills Details 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. This includes a proven ability to architect for scalability, reliability, and performance. · 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 a software/technology customer-facing role for at least 5 years is highly relevant. · 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. This reflects the growing importance of Generative AI skills at this level. Active Google Cloud Professional Certification is highly preferred (Professional Machine Learning Engineer and/or Professional Cloud Architect), reflecting our commitment to the Google Cloud Partner Advantage ecosystem.

Skills

Cloud, Architecture

## Description

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. Team sizes for mentorship can range from


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