Delivery Manager
Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on Oct 9, 2026. EXL scores B on the Alion truth index.
We are seeking a Delivery Lead to manage the end-to-end delivery of data platform projects, including solutions leveraging Generative AI and modern data engineering architectures. This role requires strong coordination across cross-functional teams of Data Engineers, Machine Learning Engineers, Architects, and platform specialists to ensure successful implementation and business alignment
Base Compensation Range: CAD 125,000 - 145,000
The posted range is the hiring range for this role - a subset of the broader range available to employees over time - and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications.
For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits
Key Responsibilities:
- Lead full lifecycle delivery of data and AI solutions - from discovery and design through development, deployment, and adoption.
- Collaborate with Solution Architects, Data Scientists, and business stakeholders to validate functional use cases and technical feasibility.
- Manage technical risks, drive issue resolution, and ensure the quality and scalability of delivered solutions.
- Oversee sprint planning, release management, and production deployment, including post-release monitoring and performance tuning.
- Foster strong relationships with business users, enterprise architects, and vendor partners to ensure value-driven outcomes.
Required Skills:
- 10 +years of experience in delivering enterprise-scale data and AI projects
- Strong grasp of data architecture, data pipelines, prompt engineering, model deployment, and evaluation metrics.
- Excellent communication skills and ability to bridge technical and business teams effectively.
bachelors in engineering or related field