Technical Program Manager

Technical Program Manager (TPM) Role Overview
The Technical Program Manager (TPM) drives complex technical programs from planning through execution and delivery.
At redBus, TPMs are expected to be technical leaders, execution drivers, and force multipliers who bring clarity to ambiguity, improve delivery predictability, and use AI and automation to make teams more effective.
Whether youre helping launch new features, scaling core backend APIs, setting up regional compliance, or introducing new AI capabilities, you will be the key collaborative partner who connects the dots, resolves cross-team dependencies, and keeps everyone moving forward smoothly.
Key ResponsibilitiesProgram Delivery

• Cross-Domain Leadership: Lead complex technical programs, geo-expansions, and cross-functional initiatives across the organization.
• Goal Translation : Translate business goals into clear plans, milestones, ownership, and measurable outcomes.
• Proactive Risk Management : Identify risks, dependencies, and blockers early and drive mitigation plans to closure.
• Strategic Partnering : Partner with Product and Engineering on prioritization, capacity alignment, and execution trade-offs.
• Release Readiness : Drive release readiness and confidence across Engineering, QA, Infrastructure, Product, and Operations.
• Stakeholder Governance : Communicate program health, risks, decisions, and trade-offs clearly to stakeholders and leadership.
  

Engineering Execution

• Architectural Review: Participate actively in architecture, API, integration, and solution reviews to identify technical risks and dependencies early.
• Sprint Readiness (DoR): Drive and enforce a strong Definition of Readiness (DoR) before sprint commitment.
• Quality & Shift-Left Maturity: Promote Shift-Left practices by aligning Development and QA early, ensuring test case definition before coding begins.
• Operational Metrics: Track and optimize delivery metrics such as delivery predictability, defect density, build delays, and release quality.
• Continuous Improvement: Improve planning, execution, governance, and cross-team collaboration through data-driven interventions and post-sprint RCAs.
  

AI Program Leadership

• AI Feature Delivery: Drive AI/GenAI initiatives (e.g., smart recommendation models, chat assistants, predictive routing) from proof-of-concept through to production and adoption.
• Collaborative Formulation: Partner with Product, Engineering, Data, and ML teams to define scope, execution plans, and success metrics.
• AI Success Metrics: Track AI-specific performance metrics, including model accuracy, latency, reliability, token costs, and adoption.
• Safety & Quality Guardrails: Ensure AI solutions consider privacy, data security, model quality, continuous monitoring, and graceful fallback mechanisms.
  

AI, Automation & Tooling (Internal Productivity)

• Agile Tooling Innovation: Build or prototype lightweight tools, dashboards, automations, and AI-powered workflows to optimize program tracking.
• Process Automation: Use AI to improve requirement analysis, risk detection, dependency tracking, reporting, and release readiness.
• Eliminating Friction: Automate repetitive program and engineering workflows using APIs, scripting, AI tools, or low-code platforms.
• Scalable Mechanisms: Identify manual operational processes that can be replaced with scalable automation.
  

QualificationsRequired Qualifications

• Educational Background: Bachelors Degree or equivalent experience in Computer Science, Engineering, IT, or a related technical field.
• Agile Foundation: Strong understanding of SDLC, Agile methodologies, APIs, system integrations, testing, and release management.
• Strategic Oversight: Strong program management skills across planning, execution, risk, dependency, and stakeholder management.
• Technical Depth: Ability to understand technical architectures, microservices, and databases, working effectively alongside engineers and architects.

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• Professional Attributes: Strong analytical, communication, and problem-solving skills; ability to manage multiple priorities in a fast-paced environment.
• Ownership Mindset: A clear bias toward execution, problem-solving, and measurable outcomes.
• Tech Adaptability: Ability to quickly learn and adopt emerging technologies, including modern AI tools and frameworks.
  

Preferred Qualifications

• Engineering Roots: Prior hands-on experience as an SDE, SDET, DevOps Engineer, Data Engineer, or a similar technical role.
• Delivery History: 2+ years of software engineering or technical delivery experience before or alongside transitioning into Program Management.
• Program Diversity: Experience driving AI/ML, GenAI, Data, Platform, or Developer Productivity programs.
• System Integration: Experience building internal tools, dashboards, JIRA automations, or productivity solutions.
• Certifications: CSM, CSP, PMP, SAFe, or equivalent certification is a plus.
  

What Success Looks Like
A successful TPM at redBus acts as an operational anchor:

• Predictable Velocity: Improves delivery predictability and release confidence (aiming for the target 90%–100% performance band).
• Proactive Mitigation: Identifies and resolves risks before they turn into blockers.
• Backlog Maturity: Drives strong sprint and release readiness, ensuring zero features slip into development with open dependencies.
• Quality Improvement: Drives down post-production defect leakage through early Dev–QA alignment.
• Simplified Delivery: Simplifies complex, multi-team global cross-team execution.
• AI Delivery: Successfully drives experimental AI initiatives into production.
• Operational Leverage: Uses automation to reduce manual coordination and builds scalable mechanisms that dramatically improve engineering productivity.
  

At redBus, the TPM is expected to operate as a technical program leader, AI enabler, collaborative problem solver, and execution owner.