Delivery Lead - AI

eClerx•Austin, TX

5h•Onsite

About The Position

The Delivery Leader – AI Engineering is a senior executive accountable for the end-to-end delivery of complex, high-impact AI Engineering programs across a portfolio of strategic client accounts. This leader bridges technical depth with delivery excellence—ensuring that AI solutions are shipped on time, within scope, and with measurable business value. Operating at the intersection of engineering, product, and client strategy, this individual drives consistency, quality, and growth across multiple concurrent programs. This role demands a rare combination of hands-on AI/ML knowledge, enterprise delivery discipline, and executive client relationship management. The Delivery Leader cultivates high-performing teams, establishes delivery frameworks scaled for AI complexity, and serves as the senior accountability point across accounts.

Requirements

10+ years of experience in technology program delivery, with at least 4 years leading AI/ML or data engineering programs at scale
Proven track record managing multi-million-dollar, multi-account delivery portfolios in a consulting, systems integration, or technology services environment
Deep understanding of the AI/ML project lifecycle: data strategy, feature engineering, model development, MLOps, and production AI systems
Strong executive presence with demonstrated ability to build and maintain C-level client relationships
Experience leading cross-functional, geographically distributed teams of 20+ across engineering, data science, and architecture disciplines
Proficiency in enterprise agile delivery (SAFe, Scrum, Kanban) and program governance frameworks
Excellent communication and storytelling skills—ability to articulate complex AI concepts to both technical and business audiences

Nice To Haves

Background in software engineering, data science, or ML engineering (hands-on experience a strong differentiator)
Experience deploying LLM-powered solutions, generative AI products, or agentic AI systems in enterprise environments
Familiarity with major cloud AI platforms: AWS SageMaker, Azure ML, Google Vertex AI
Knowledge of AI governance, responsible AI frameworks, and enterprise data privacy regulations (GDPR, CCPA, HIPAA)
PMP, PgMP, or SAFe Program Consultant (SPC) certification
MBA or advanced degree in Computer Science, Engineering, or a related field
Industry expertise in financial services, healthcare, retail, or manufacturing (sectors with complex AI use cases)

Responsibilities

Own end-to-end delivery accountability across a portfolio of AI Engineering projects spanning multiple client accounts and industry verticals
Establish and govern delivery frameworks, methodologies, and standards tailored for AI/ML program complexity (e.g., iterative ML pipelines, model governance, data readiness gates)
Drive project planning, milestone tracking, risk management, and executive reporting across all active engagements
Proactively identify delivery risks—technical debt, scope creep, resource gaps—and execute mitigation strategies
Ensure consistent application of delivery best practices: agile ceremonies, sprint cadences, retrospectives, and continuous improvement loops
Serve as the executive delivery sponsor for strategic accounts, building trusted C-suite and VP-level relationships
Lead quarterly business reviews (QBRs), program status briefings, and executive steering committees
Translate complex AI/ML delivery status into clear business narratives for non-technical client stakeholders
Act as the primary escalation point for delivery issues, exercising judgment to resolve conflicts quickly while preserving client relationships
Partner with account management and sales teams to identify expansion opportunities and support commercial growth
Lead, mentor, and develop a multi-disciplinary team of delivery managers, ML engineers, data engineers, and solution architects
Build a high-performance delivery culture centered on ownership, transparency, and continuous learning
Collaborate with resource management to ensure optimal staffing of AI talent across accounts
Foster psychological safety and inclusive team dynamics, enabling diverse teams to do their best work
Identify capability gaps and partner with L&D to upskill delivery teams on emerging AI technologies and practices
Provide technical oversight and architectural guidance on AI/ML solution design, ensuring technical decisions align with delivery timelines and client objectives
Govern model lifecycle management across accounts: from data ingestion and model training to evaluation, deployment, and monitoring
Champion responsible AI practices including fairness assessments, bias mitigation, explainability requirements, and compliance controls
Stay current with frontier AI developments (LLMs, agentic AI, multimodal systems) and advise clients on strategic adoption paths
Partner with enterprise architecture teams to ensure AI solutions integrate securely within client technology ecosystems
Define and track KPIs for delivery health across the portfolio: on-time delivery, utilization, client satisfaction (NPS/CSAT), and margin performance
Drive standardization through reusable delivery assets, playbooks, and accelerators that reduce time-to-value across AI engagements
Contribute to practice development: thought leadership, case studies, go-to-market narratives, and proposal development
Support hiring and team growth, establishing the delivery function as a center of AI delivery excellence