Director - Transformation Lead

Role: Director - Transformation Lead

Role Summary

The Director Transformation is a hands-on leader who acts as one of our most senior technical experts in the field. This is a unique, dual-mission role. Externally, you will engage with our most strategic clients in a "forward-deployed" capacity, leading technical workshops to design and integrate our data solutions into their complex ecosystems. Internally, you will use these client insights to architect and build the next generation of AI-powered tools and workflows, radically optimizing our own data annotation processes. Your ultimate goal is to create an unbeatable competitive advantage by continuously improving our efficiency, quality, and delivery, directly reducing our clients' Total Cost of Ownership (TCO).

Responsibilities

Client Solution Engineering & Integration (External Focus)

• Lead Technical Discovery & Solution Design: Post-sale, partner with the Solutioning team to lead deep-dive technical workshops with clients. Deconstruct their current workflows, data challenges, and business objectives.
• Architect Custom Integration Plans: Design and map out how our platform and services will integrate seamlessly into the client's existing AI/ML pipelines and infrastructure.
• Act as the "Art of the Possible" Guide: Serve as the primary technical advisor to clients, demonstrating how our advanced capabilities, custom tools, and innovative workflows can solve their most difficult data challenges and accelerate their AI initiatives.
• Bridge to the Platform Team: Translate complex client requirements into precise technical specifications and user stories for our core Platform Deployment & Management team, ensuring our platform roadmap is directly informed by real-world client needs.
• Oversee Proofs of Concept (POCs): Lead and develop targeted POCs to prove the value and viability of our solutions within the client's environment, de-risking large-scale engagements.
  
  

Internal Process Transformation & Innovation (Internal Focus)

• Drive Process Excellence: Be the owner of operational efficiency for our data annotation workforce. Continuously analyze our Human-in-the-Loop (HITL) workflows to identify and eliminate bottlenecks.
• Develop AI-Powered "Co-Pilots" and Accelerators: Architect, build, and deploy a portfolio of internal tools and intelligent agents that augment our human annotators. This includes automated quality checks, predictive assistance, and workflow-agnostic automation scripts.
• Engineer "Safety Nets": Design and implement automated quality assurance (QA) systems and predictive monitoring to ensure we consistently exceed client SLAs for accuracy and throughput.
• Champion Human-in-the-Loop Optimization: Leverage Generative AI, LLMs (fine-tuning, RAG), and computer vision models to create systems that make our human workforce smarter, faster, and more accurate.
• Quantify Business Impact: Develop and maintain a framework to measure the ROI of your transformation initiatives, clearly demonstrating their impact on project margins, delivery speed, and client TCO.
  
  

Skills & Qualifications

Required Qualifications:

• Experience: 12+ years in a technology field, with at least 5 years in a senior, client-facing technical role such as a Solutions Architect, Forward Deployed Engineer, Professional Services Consultant, or Transformation Lead.
• Applied AI & Process Automation: Proven, hands-on experience building and deploying production-grade AI/ML systems specifically for process automation and optimization. This is more important than pure research experience.
• Generative AI Stack Expertise: Deep, practical experience with the modern Generative AI stack, including LLMs (fine-tuning, RAG), agentic frameworks, and vector databases. You must have built things with these technologies.
• Hybrid Skillset: A demonstrated ability to operate at the intersection of deep technology and business strategy. You must be able to write code and architect systems, but also create a compelling business case and present to a client executive.
• Cloud Architecture: Deep architectural expertise in one or more major cloud platforms (AWS, Azure, GCP), including their managed AI/ML services (e.g., SageMaker, Vertex AI).
  
  

Preferred Qualifications

• Consultative Mindset: A natural ability to listen, diagnose problems, and guide clients and internal teams toward elegant, effective solutions.
• Data Annotation Domain Knowledge: Direct experience with data annotation platforms, data quality challenges, and the operational dynamics of large-scale data labeling workforces.
• Experience Building Internal Tools: A track record of identifying an internal business need and building a software solution to address it, driving measurable efficiency gains.
• An advanced degree (master's or PhD) in Computer Science, AI, or a related field is a strong plus.
• A portfolio of projects (e.g., GitHub) or detailed case studies demonstrating your work in building AI-driven solutions.