Delivery Manager

Remote Work
Full-Time
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Why Join Us? (Benefit)

We are looking for a Delivery Manager who can lead engineering delivery with a strong balance of technical depth, product understanding, and quality ownership. This role will be responsible for ensuring that every release from the assigned engineering team meets Talentlytica’s delivery standards across functionality, performance, security, data integrity, and user experience. The ideal candidate has hands-on engineering experience, strong familiarity with XP practices, and the ability to guide teams in delivering reliable, secure, and scalable solutions for Talentlytica’s assessment platform.

Position Overview

Requirement

  • Minimum 4 years of hands-on software engineering experience, with at least 2 years in a technical lead or delivery lead capacity.
  • Proven experience owning engineering delivery quality end-to-end, from planning and development to release readiness.
  • Practical working knowledge of Go and/or Rust for backend services, and React.js/Next.js for frontend development.
  • Strong ability to review code, identify architectural issues, and guide engineers through technical challenges.
  • Deep familiarity with Extreme Programming practices, including TDD, Pair Programming, Continuous Integration, Simple Design, Collective Code Ownership, and iterative planning.
  • Experience working with structured acceptance criteria frameworks, such as Category Acceptance Criteria or similar quality gate frameworks.
  • Strong understanding of secure coding principles, OWASP Top 10, authentication/authorization patterns, and data protection practices.
  • Practical experience with AI-assisted development tools such as GitHub Copilot or LLM assistants, with the ability to guide responsible usage within the team.
  • Strong cross-functional communication skills, with the ability to represent engineering in product discussions, explain technical constraints, and negotiate realistic delivery timelines.
  • Proven ability to mentor and grow engineering talent through feedback, pair programming, and a psychologically safe team environment.
  • Experience with cloud platform operations such as GCP or AWS, including CI/CD, observability, deployment pipelines, and infrastructure concerns for high-availability systems.
  • Responsibility

    • Own end-to-end delivery quality for the assigned engineering team, ensuring every release meets key quality standards across functional correctness, performance, security/data protection, data integrity, and UI/UX compliance before reaching production.
    • Lead and facilitate Extreme Programming practices within the team, including Planning Game, iterative delivery cycles, Pair Programming, Test-Driven Development, and continuous integration.
    • Define and govern Category Acceptance Criteria in collaboration with the Product Owner and stakeholders to ensure all user stories have clear, complete, and measurable acceptance standards before development begins.
    • Serve as the technical decision authority for the team by facilitating architectural decisions, reviewing critical code, enforcing coding standards, and ensuring technical outputs meet platform-grade standards.
    • Drive responsible AI-assisted development by setting clear norms for using tools such as GitHub Copilot or LLM-based assistants without compromising security, data integrity, or code ownership.
    • Coordinate alignment between engineering teams, including managing dependencies, shared components, and roadmap synchronization to prevent delivery bottlenecks.
    • Mentor and grow engineers by supporting technical development in Go, Rust, React.js, security practices, and XP values such as collective ownership, sustainable pace, and simple design.
    • Translate business and product requirements into executable technical plans, acting as a bridge between Product, Design, and Engineering while maintaining realistic delivery commitments.
    • Monitor and improve delivery health by tracking iteration throughput, acceptance criteria pass rates, regression trends, and CI pipeline stability, then taking proactive action when needed.

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