Practice Architect-AI/ML

TEKsystems•Austin, TX

2d•$136,000 - $204,000•Remote

About The Position

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: The Practice Architect I (PA I) – AI/ML position is a leadership role responsible for managing multiple consulting and delivery projects and account teams/programs, with a defined focus on machine learning and artificial intelligence solutions. The Practice Architect I provides consulting leadership and delivery assurance for clients across a range of internal and externa l functions, including Consulting, Account Interaction, Service Delivery, and Practice Delivery. In addition to traditional consulting and delivery management responsibilities, this role requires hands-on and architectural experience across the AI/ML lifecycle, including building machine learning models, operationalizing them at scale in production environments through MLOps practices, and supporting ongoing model performance, governance, and reliability. Experience with Generative AI technologies and the design and implementation of Agentic AI workflows is essential, with an expectation of at least 1–2 years of direct experience delivering GenAI and agent-based solutions in real-world environments. The position of Practice Architect I is distinguished from more senior Practice Architect roles by the nature and scale of engagements; deal sizes range from transactional solutions of less than $1M to multi-year outsourcing solutions exceeding $10M. As a first-level Practice Architect, the PA I is expected to possess the experience and background required to perform all core duties for AI/ML -focused consulting and delivery engagements. These duties include resource management, AI/ML solution and deliverables development, project planning and execution, adherence to contract attributes and costing, customer interaction, and other key aspects of solution-based managed services. Engagements will typically be delivered for North American clients, either remotely or at customer locations within North America. The PA I is expected to demonstrate sufficient depth to contribute to complex, large-scale, or fully outsourced AI/ML programs, collaborate effectively within cross-functional teams, and provide architectural and delivery input into broader programs. This role may require up to 50% travel.

Requirements

Strong conceptual and analytical skills, demonstrating out-of-the-box problem solving, including the ability to apply AI/ML and Generative AI concepts to complex business and technical challenges
Proven ability to appropriately prioritize and plan complex work in a rapidly changing environment, particularly across AI/ML, MLOps, and GenAI initiatives with evolving requirements and dependencies.
Demonstrated experience designing, evaluating, and guiding Generative AI solutions, including large language model (LLM) use cases, prompt engineering strategies, retrieval-augmented generation (RAG), and agentic or multi-step AI workflows.
Ability to collaborate with machine learning, engineering, cloud, security, and business stakeholders to translate GenAI capabilities into scalable, production-ready solutions.
Team player with experience leading and collaborating across teams to deliver successful solutions, including cross-functional AI/ML and GenAI delivery teams.
Excellent oral and written communication skills (English language), with the ability to explain GenAI and ML concepts to both technical and non-technical audiences, including executives.
Superior people and personnel management skills, including mentoring teams working on AI/ML, MLOps, and Generative AI solutions, and fostering best practices and delivery excellence.

Nice To Haves

Relevant certifications in the subject matter area(s)

Responsibilities

Gain a clear understanding of customers’ business objectives, data landscape, and technical requirements for AI/ML and Generative AI solutions based on the agreed solution architecture and Statement of Work (SOW).
Understand, develop, and mature AI/ML and GenAI solution designs by collaborating with customers and internal stakeholders to manage expectations, resolve architectural, data, model, and delivery issues, and ensure alignment with production and scalability goals.
Facilitate internal communication and coordinate the assembly of cross-functional AI/ML delivery teams, including data science, MLOps, cloud engineering, security, practice support, and account team members for new engagements.
Consolidate and communicate delivery status, model readiness, MLOps maturity, and agreed costing information across project stakeholders to ensure transparency and alignment throughout the engagement lifecycle.
Ensure delivery escalation procedures are clearly defined, addressed, and communicated to clients, consultants, and management, particularly for risks related to data quality, model performance, GenAI behavior, infrastructure, and compliance.
Implement and oversee a knowledge management strategy for AI/ML engagements, ensuring effective knowledge transfer from sales and solutioning to delivery teams, including GenAI architectures, agentic workflows, and operational considerations.
Perform delivery risk and issue management across AI/ML and GenAI programs, proactively identifying risks related to data, models, infrastructure, governance, and security, and facilitating timely resolution with appropriate stakeholder communication.
Identify, manage, and coordinate delivery change control processes for AI/ML and Generative AI engagements, including changes related to data availability, model scope, infrastructure, MLOps pipelines, and evolving GenAI requirements.
Perform periodic AI/ML project and program analysis, including architecture reviews, model lifecycle assessments, MLOps and GenAI workflow health checks, in collaboration with practice and delivery resources.
Assess and enhance customer reference-ability by ensuring successful delivery of AI/ML and GenAI solutions and establishing trusted advisory relationships with customers and account team members.
Refine the AI/ML practice pipeline and product line attributes based on delivery metrics, adoption trends, model performance, and alignment with market demand, emerging GenAI capabilities, and agentic AI patterns.
Support the development and execution of Account Strategies by identifying AI/ML and Generative AI opportunities and collaborating with internal stakeholders to align technical capabilities with client business objectives.
Capture, develop, and refine AI/ML, MLOps, and Generative AI intellectual property (IP) derived from projects and programs, including reference architectures, accelerators, agentic AI patterns, and reusable assets for training and delivery.
Coordinate with subject matter experts to define and standardize best practices for AI/ML and GenAI delivery, including model development standards, MLOps practices, responsible AI considerations, and continuous delivery improvements.
Understand and manage customer requirements (delivery and environmental factors) to ensure contract understanding and acceptance for deliverables, cost, contract type, timeline, risk and assumptions, and customer satisfaction.
Ensure delivery methodology is understood by team from project initiation to project closeout; sales/solution to delivery knowledge transfer.
Financial and contractual responsibility for engagement profitability.
Maintain awareness for additional business opportunities and support pursuit of future business through quality results and escalation to internal stakeholders when additional business opportunities may present themselves.
Ensure delivery management methodology is followed on all client opportunities.
Mentor, manage and develop product/project team members. Team size varies from 3 team members up to 8-10 team members.
Conduct annual reviews and provide feedback throughout the year on employee performance where required.
Ensure Human Resources policies and procedures are communicated and executed according to internal and consultant HR policies.