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- Tasks: Lead delivery planning and execution for AI-driven product data enrichment.
- Company: Join a forward-thinking tech company focused on AI innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Be at the forefront of AI technology and make a real impact in product discovery.
- Qualifications: Experience in delivery management, AI/ML, and data integration preferred.
- Other info: Collaborative team environment with exciting projects and career advancement potential.
The predicted salary is between 36000 - 60000 ÂŁ per year.
Enrich AI is Rezolve’s product data enrichment platform. It uses AI/LLM driven orchestration to enrich product catalog data (attributes, classifications, metadata) to improve search quality and product discovery.
Current delivery surface area includes:
- Infrastructure stabilization/scaling and environment provisioning (working with SRE + vendor such as Aiven).
- AI output quality improvements (audits, golden dataset testing).
- Orchestration optimization (reduce LLM calls / cost-to-enrich).
- DataHub integration for automated data flows (cross-project dependency on DIM).
- Rules system (post-enrichment processing) and related frontend ops workflows.
- Distributed team delivery (incl. Rezolve India team onboarding started 2026-01-05).
Current code base surface area includes:
- Backend/API: enrich-ai is an Nx monorepo POC aiming to replace existing Enrich APIs, building a federated GraphQL graph (Node.js/NestJS/Prisma; GraphQL federation/Apollo Router; GraphQL Yoga; Pothos; tRPC).
- UI integration: command-center-enrich is a React 18 app/plugin-style repo (Material UI + styled-components) that integrates an Enrich console package into Command Center and is enabled via feature flag.
Own predictable, transparent delivery for Enrich AI across infrastructure, AI quality, and integration initiatives; ensure the team can plan, execute, and ship with clear priorities, minimal delivery friction, and reliable stakeholder communication.
Key responsibilities
- Delivery planning & execution: Run weekly planning/triage and drive a consistent delivery cadence aligned to the team’s “Weekly Highlight Reports” structure. Maintain delivery plans in Jira (including Advanced Roadmaps plan where applicable), ensuring scope, sequencing, and dependencies are explicit. Convert goals/initiatives into executable epics/stories with clear acceptance criteria and measurable outcomes.
- Dependency & blocker management (critical path): Actively manage cross-team dependencies, notably DataHub Enrich integration blocked by DIM work. Set up explicit dependency tracking (Jira links, dependency board, weekly check-ins) and publish status/ETAs with confidence levels.
- Release & operational readiness: Coordinate releases and operational readiness with SRE/Operations; ensure run books, rollbacks, and monitoring/alerting expectations are met. Drive risk reviews for infra changes, vendor constraints, and environment provisioning.
- Quality and AI outcomes management: Ensure AI quality work is planned and communicated with clear, reviewable outcomes. Ensure the team can report AI improvements in a way leadership can understand (quality, cost, throughput).
- Jira/Confluence hygiene + reporting: Ensure Jira reflects reality (status discipline, WIP limits, aging work review, clear definitions of done). Produce crisp weekly delivery updates and bi-weekly CTO-ready highlights (accomplished/ planned / risks / decisions).
Preferred Experience (strong Plus)
- AI/ML product delivery experience (MLOps, model/LLM quality evaluation, experiment cadence).
- Data pipeline/integration delivery experience (ETL, data platforms, system-to-system integrations).
- Experience with PIMs (Product Information Management) / PIM workflows.
- Familiarity with CI/CD and cloud vendor management.
- Familiarity delivering GraphQL/Graph federation APIs and modern TypeScript backends (Nx monorepos, NestJS).
- Familiarity coordinating frontend delivery in React ecosystems (Material UI / component libraries) and feature flag rollouts.
Key relationships
- Engineering lead (Enrich)
- SRE / platform engineering
- DIM / DataHub team (dependency partner)
- Product and Operations stakeholders
- Professional Services (incl. India team)
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Delivery Manager employer: Rezolve Ai
Contact Detail:
Rezolve Ai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Delivery Manager
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Enrich AI or similar companies. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Prepare for interviews by diving deep into the company’s products and services. Understand how they use AI/ML in their delivery processes. This shows you're genuinely interested and ready to contribute from day one!
✨Tip Number 3
Practice your delivery management skills! Think about how you would handle dependencies and blockers in real scenarios. Being able to discuss your approach confidently can really impress interviewers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re keen on being part of our team!
We think you need these skills to ace Delivery Manager
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Delivery Manager role. Highlight your experience with AI/ML product delivery and data pipeline integration, as these are key areas for us at Enrich AI.
Showcase Your Skills: Don’t just list your skills; demonstrate them! Use specific examples from your past experiences that align with the responsibilities mentioned in the job description, like managing dependencies or coordinating releases.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate crisp communication, so make sure your application reflects that by avoiding jargon and unnecessary fluff.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role without any hiccups!
How to prepare for a job interview at Rezolve Ai
✨Know Your Stuff
Make sure you understand the ins and outs of delivery management, especially in the context of AI and data enrichment. Brush up on your knowledge of tools like Jira and how to manage dependencies effectively. Being able to discuss specific examples from your past experience will show that you’re not just familiar with the concepts but have actually applied them.
✨Showcase Your Communication Skills
As a Delivery Manager, clear communication is key. Be prepared to discuss how you've managed stakeholder expectations and communicated project statuses in the past. Use examples that highlight your ability to keep everyone in the loop, especially when it comes to managing cross-team dependencies.
✨Prepare for Technical Questions
Expect some technical questions related to AI/ML product delivery and data integration. Familiarise yourself with concepts like GraphQL, CI/CD, and cloud vendor management. You might be asked to solve a problem on the spot, so practice articulating your thought process clearly and confidently.
✨Demonstrate Your Problem-Solving Skills
Be ready to discuss how you've tackled challenges in previous roles, particularly around risk management and operational readiness. Think of specific scenarios where you identified a blocker and how you resolved it. This will show that you can think critically and act decisively under pressure.
