Technical Program Manager Data & AI Platform

Kapitus is building a next-generation enterprise data and AI capability that replaces hundreds of legacy analytics workflows with governed reusable business data products and moves the organization from producing reports to producing decisions.

We are looking for an experienced Technical Program Manager to run the day-to-day execution of this program. This is not a status-reporting role. You will own the integrated delivery plan across concurrent workstreams data architecture and platform engineering governed business data products MDM and ontology semantic and consumption layers data governance ML/MLOps and GenAI/agentic AI. This will be delivered by a mix of internal teams and external consulting partners across onshore nearshore and offshore locations. You will keep a milestone-gated tightly budgeted program on schedule hold vendors to their commitments and be credible in front of both engineers and executives.

You report directly to the program executive leading the Data & AI organization and serve as the operational execution lead for the transformation program. You are not the architect the product owner the engineering lead or the Scrum Master; you are the person who turns architecture decisions into plans plans into accountable work and work into accepted evidenced outcomes.

What you will do:

Program delivery and planning

• Own and maintain the single authoritative integrated delivery plan across internal teams and all delivery partners reconciling vendor plans into one program baseline rather than managing independent project schedules covering sequencing cross-stream dependencies critical path resource loading and capacity and milestone readiness.

• Own end-to-end readiness of each data product delivery wave: design source readiness build governance controls verification business validation serving and consumption readiness production release and legacy decommissioning. Code complete is not product complete.

• Run the programs delivery cadence end to end sprint ceremonies backlog alignment across streams RAID (risks actions issues decisions) management and weekly executive reporting.

• Manage milestone-gated delivery: track work against defined acceptance gates (design baseline ready-to-build vendor verification business/customer validation production acceptance closeout) and make sure nothing is claimed complete that has not passed its gate.

• Track budget consumption against not-to-exceed envelopes and estimate-at-completion forecasts; surface variances early with options not surprises.

• Plan realistically distinguish contracted capacity from productive capacity and keep utilization assumptions explicit and defensible.

Vendor and partner management

• Manage day-to-day execution with external consulting partners: statement-of-work scope deliverable acceptance change control and separation of duties between build and validation teams.

• Coordinate distributed teams across time zones and keep handoffs between onshore design and offshore engineering clean.

• Prepare the evidence trail delivery plans defect logs verification records that supports invoice approval and milestone release decisions.

• Maintain traceability from contractual deliverables through program requirements epics and stories acceptance criteria validation evidence milestone gates and commercial approvals so every invoice correlates to accepted work.

Technical coordination

• Understand the work well enough to challenge it: data product design ELT pipeline builds legacy workflow migration and decommissioning semantic layer and BI serving data quality and governance controls and ML/AI platform components.

• Run dependency management between platform hardening data product waves governance readiness and AI platform build-out.

• Coordinate governance readiness alongside product delivery ownership critical-data-element and sensitivity classification lineage data quality controls metadata policy conformance and catalog readiness so governance ships with the product rather than following it months later.

• Manage cross-functional readiness dependencies spanning architecture security/risk platform governance procurement and production operations; ensure approvals and unresolved decisions are visible on the critical path and driven to closure.

• Facilitate architecture and design decision forums; track exceptions and conformance debt to closure.

Stakeholder management

• Be the connective tissue between business owners architecture engineering governance finance/procurement and executive sponsors.

• Communicate program status in plain language accurate evidence-based and honest about risk.

• Drive closure not coordination alone: drive timely decisions identify accountable owners escalate unresolved dependencies early and challenge unsupported status or completion claims.

What were looking for:

• 10 years delivering complex technology programs

• 5 years leading enterprise data/platform transformation programs involving multiple concurrent technical teams. Backgrounds that combine program leadership with engineering management technical delivery consulting data platform delivery or solution delivery are strongly valued; demonstrated technical delivery depth matters more than title progression alone.

• Consulting or professional services delivery background. You have run client-facing programs under tight timelines fixed budgets and contractual milestone commitments and you know how to manage scope change control and acceptance in that environment (either side of the table: delivery firm or client program office).

• Deep practiced agile delivery skills with Scrum Kanban and scaled/hybrid models; you can run ceremonies coach teams manage backlogs across multiple pods and blend agile execution with milestone-gated commercial governance.

• Modern cloud data platform fluency and hands-on program experience with Snowflake and/or Databricks and working knowledge of the surrounding ecosystem: ELT/transformation frameworks (e.g. dbt) orchestration data catalogs and lineage tooling BI/semantic layers and legacy workflow migration (e.g. Alteryx SSIS or similar).

• Strong AI/ML literacy you understand the ML lifecycle (feature engineering training validation deployment monitoring) MLOps concepts and the emerging GenAI/LLM stack (retrieval agents model risk considerations) well enough to plan and de-risk AI workstreams.

• Vendor management experience managing multi-vendor delivery against SOWs rate cards and NTE budgets including offshore/nearshore delivery models.

• Financial discipline comfortable owning budget tracking forecasting (EAC) and the commercial mechanics of T&M and milestone-based contracts.

• Excellent communication skills with crisp written and verbal communication; able to produce executive-ready status materials and defend the numbers behind them.

Additional Preferred Skills:

• Experience in financial services in lending banking fintech or another regulated environment and familiarity with model risk management and data governance expectations in regulated industries.

• Experience with data product operating models (data mesh / data product thinking data contracts certified metrics).

• Certifications such as PMP PMI-ACP CSM/A-CSM SAFe or equivalent are valued as evidence of rigor not as a substitute for demonstrated delivery experience.

• Snowflake Databricks or cloud (AWS/Azure) certifications.

• Experience standing up program governance from scratch: gate definitions RAID discipline delivery evidence standards and vendor validation streams.

Kapitus Total Rewards Package Includes:

• Competitive Base SalaryRange of $120400-$193200 Kapitus is providing this as a good faith salary range to comply with applicable law. The applicants final salary will depend on a number of factors including the applicants geographic location skills and experience.

• Annual Incentive Compensation Eligibility Up to 10% annually