Technical Delivery Manager

We are looking for a seasoned Technical Program Manager to lead and manage multiple cross-functional engineering pod teams based in Hyderabad. This role requires strong technical depth, hands-on understanding of modern full stack engineering practices, cloud-native platforms, DevSecOps, and practical experience using AI and Gen AI platforms to improve engineering productivity, delivery predictability, quality, and operational excellence.

The ideal candidate should have prior experience managing complex technology programs involving distributed engineering teams, product owners, architects, developers, QA engineers, DevOps teams, security teams, and business stakeholders. The candidate must be comfortable operating at both strategic and execution levels — driving roadmap alignment, technical delivery, architecture discussions, release governance, dependency management, risk mitigation, and executive-level reporting.

This is not a pure project management role. The candidate is expected to bring strong technical judgment, understand engineering trade-offs, challenge solution approaches where required, and guide teams toward scalable, secure, maintainable, and AI-enabled delivery practices.

Lead multiple engineering pod teams delivering full stack, cloud-native, and enterprise-grade digital applications.

Own end-to-end program execution across planning, design, development, testing, release, deployment, and production support.

Drive delivery predictability across multiple pods by managing scope, schedule, dependencies, risks, milestones, and release commitments.

Partner with product owners, architects, engineering managers, QA leads, DevOps teams, security teams, and business stakeholders to ensure successful execution.

Establish clear operating rhythms across sprint planning, backlog refinement, architecture reviews, dependency tracking, release planning, and production readiness.

Monitor execution health across pods and proactively address blockers, capacity gaps, technical risks, and cross-team dependencies.

Drive alignment between business objectives, product priorities, technical architecture, and delivery execution.

Ensure programs are delivered with strong focus on quality, security, scalability, maintainability, and operational stability.

Facilitate technical design discussions across .NET Core, Angular, REST APIs, microservices, cloud platforms, databases, DevSecOps, and integration platforms.

Partner with architects and senior engineers to validate solution approaches, identify architectural risks, and ensure adherence to enterprise standards.

Drive technical governance across application architecture, API design, cloud integration, security, performance, observability, and deployment practices.

Ensure engineering teams follow clean architecture, SOLID principles, secure coding practices, CI/CD standards, and cloud engineering best practices.

Track and manage technical debt, platform modernization initiatives, production stability issues, and engineering improvement plans.

Support teams in resolving production issues related to performance, scalability, reliability, integrations, cloud services, and deployment pipelines.

Ensure delivery teams adopt appropriate engineering metrics, including sprint predictability, defect leakage, deployment frequency, change failure rate, code quality, test coverage, and production incident trends.

Drive responsible adoption of AI and Gen AI tools across engineering pods to improve productivity, code quality, documentation, testing, and problem-solving.

Enable teams to use platforms such as GitHub Copilot, ChatGPT Enterprise, Azure OpenAI, Amazon Q, Gemini , or similar enterprise-approved AI platforms.

Identify practical AI use cases across software delivery, including code generation, refactoring, unit test generation, API documentation, technical design documentation, defect analysis, and security review support.

Establish AI usage guardrails aligned with enterprise security, data privacy, compliance, intellectual property, and responsible AI policies.

Partner with engineering and security teams to evaluate AI-assisted development workflows and ensure safe adoption.

Track productivity and quality improvements resulting from AI-enabled engineering practices.

Promote a culture of AI-assisted engineering while ensuring human accountability for design, code quality, security, and production outcomes.

Lead agile execution across multiple pods using Scrum, Kanban, SAFe, or hybrid delivery models.

Drive consistent sprint ceremonies, backlog hygiene, estimation practices, release planning, and execution governance.

Ensure CI/CD pipelines, automated deployments, quality gates, code reviews, test automation, security scans, and release approvals are integrated into delivery workflows.

Partner with DevOps and platform teams to improve deployment reliability, environment stability, monitoring, logging, and incident response.

Ensure production releases meet defined entry and exit criteria, including quality, security, performance, and operational readiness checks.

Drive continuous improvement across engineering processes, agile maturity, DevSecOps adoption, and delivery effectiveness.

Provide clear, concise, and data-driven program updates to senior leadership, including Directors, VPs, and CXO-level stakeholders where required.

Communicate program status, risks, dependencies, financial impacts, delivery trade-offs, and mitigation plans with appropriate executive clarity.

Prepare roadmap views, release dashboards, dependency maps, risk registers, decision logs, and program health reports.

Translate complex technical topics into business-relevant insights for non-technical stakeholders.

Drive decision-making across competing priorities, delivery constraints, architecture options, and risk scenarios.

Prior hands-on software engineering experience before moving into technical program management or engineering leadership.

Experience managing enterprise-scale modernization, cloud migration, platform transformation, or digital product engineering programs.

Exposure to regulated industries such as healthcare, fintech, insurance, life sciences, or other compliance-heavy environments.

Strong understanding of enterprise architecture governance, security reviews, audit requirements, and compliance controls.

Experience with observability platforms, production support models, SRE practices, and incident management.

Experience implementing AI-assisted SDLC practices across large engineering teams.

Understanding of responsible AI, AI governance, data privacy, secure prompt usage, and enterprise AI adoption frameworks.

The candidate should be hands-on and comfortable using AI platforms to:

Improve engineering productivity across multiple pod teams.

Assist with code review, code generation, and refactoring analysis.

Generate unit test cases and improve test coverage.

Support API documentation, architecture documentation, and technical design documentation.

Analyze technical designs, logs, defects, and production issues for faster triage.

Identify security, performance, and maintainability concerns in application delivery.

Build reusable AI-enabled workflows for engineering teams.

Promote responsible AI adoption in alignment with enterprise policies.

Ensure AI tools are used as productivity accelerators while preserving engineering accountability, security, and compliance.

At Zelis, we champion diversity, equity, inclusion, and belonging in all aspects of our operations. We embrace the power of diversity and create an environment where people can bring their authentic and best selves to work. We know that a sense of belonging is key not only to your success at Zelis, but also to your ability to bring your best each day.

Zelis is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

We are dedicated to ensuring our application process is accessible to all candidates. If you are a qualified individual with a disability and require reasonable accommodation with any part of the application and/or interview process, please email talentacquisition@zelis.com .