via Talents By Vaia
$NaNK - NaNK a year
Lead the technical design, delivery, and client engagement for complex GCP AI/ML solutions, including architecture, project management, and mentorship.
Extensive experience in GCP AI/ML, solution architecture, project leadership, and client-facing roles, with preferred certifications in GCP AI/ML.
About the position Responsibilities • 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. • Develop and implement robust, scalable, and production-grade AI/ML systems, ensuring they meet stringent performance, security, and reliability requirements for enterprise clients. • Architect and implement comprehensive MLOps 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. • 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. • 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. • 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. • 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 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. 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 Nice-to-haves • Google Cloud Professional Machine Learning Engineer • Google Cloud Professional Data Engineer Benefits • Health insurance Blue Cross Blue Shield PPO - 100 percent coverage for well visits, Individual and family options, Dental and vision options, Health savings account with annual company contribution, Coverage begins within 30 days of employment • Time off: 20 days annually plus six company holidays; After three years of employment, increases to 23 days annually plus six company holidays • Retirement savings: 401(k) with matching contribution; Profit-sharing • Tuition reimbursement: Up to a maximum of \$5,250 annually for eligible courses/programs • Additional earnings may be available through incentive programs like annual bonuses, commissions, profit sharing, etc.
This job posting was last updated on 12/12/2025