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In office (Bengaluru)
Employment
Full-Time

Confirmed on the employer's own hiring board on Sep 29, 2026. First seen by Alion on Sep 28, 2026. Weekday scores B on the Alion truth index.

Overview
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Profile match
Weekday is an Indian recruitment company that sources software engineers through referrals from other engineers rather than through job advertisements or agency databases. Its model pays working engineers to vouch for former colleagues they rate, turning informal knowledge about who is genuinely good into a searchable candidate pool that companies can hire from. Based in Bengaluru and backed by Y Combinator, the platform has layered AI screening and outbound sourcing on top of that referral network, and sells to startups and technology companies hiring in the Indian market.

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: - ( - )

Experience: 5+ yrs

Location: Bengaluru, Karnataka, India

Job Type: Full-time

As a Technical Program Manager, you will own the end-to-end operating rhythm for complex data and AI delivery programs. You will coordinate cross-functional teams, establish program cadences, track milestones and dependencies, manage risks and blockers, and ensure that delivery commitments remain visible and actionable.

You will also contribute to the development of quality assurance, ground-truth, evaluation, and release processes for data-intensive pipelines. This includes establishing human-in-the-loop sampling, measuring accuracy and precision/recall, managing annotation and adjudication workflows, and developing error taxonomies that turn recurring issues into measurable improvement opportunities.

The role combines program execution with operational and technical improvement. You will continuously identify opportunities to improve automation, efficiency, quality, and reliability while helping build scalable processes that can support future AI and enterprise data programs.

Requirements

Key Responsibilities

  • Drive complex, multi-stage programs through kickoff, execution, quality assurance, release, and delivery.
  • Establish and maintain program plans, milestones, dependencies, owners, risks, and delivery timelines.
  • Run recurring cross-functional meetings and maintain clear records of decisions, actions, owners, and deadlines.
  • Design and operate structured risk, blocker, and escalation frameworks with defined SLAs.
  • Monitor program health and proactively identify risks that could affect timelines, quality, capacity, or delivery commitments.
  • Track team capacity against active and upcoming program requirements and identify potential resource constraints.
  • Coordinate engineering, data, quality, operations, and stakeholder-facing teams across multiple workstreams.
  • Establish and improve operational processes, reporting mechanisms, dashboards, and program-management tooling.
  • Support QA loops for critical data pipelines using structured human-in-the-loop sampling and live-output assessment.
  • Define and track quality metrics including accuracy, precision, recall, completeness, consistency, and duplication rates.
  • Establish defensible ground-truth processes involving multi-annotator labelling, inter-annotator agreement, and adjudication.
  • Develop and maintain error taxonomies to identify recurring issues and drive systematic improvements.
  • Help define and enforce release gates and quality criteria for pipeline versions before production deployment.
  • Monitor pipeline throughput, batching, versioning, quality, and delivery performance.
  • Identify opportunities for automation and process optimisation to improve scalability and operational efficiency.
  • Work with technical teams to translate operational requirements into practical product, tooling, and workflow improvements.
  • Maintain clear communication across technical teams, quality/operations teams, and account-facing stakeholders.
  • Ensure delivery delays, red-line risks, unresolved blockers, and ambiguities are clearly surfaced and appropriately escalated.
  • Continuously improve program processes to establish high standards for reliability, quality, and predictable delivery.

What Makes You a Great Fit

  • 5+ years of experience in technical program management, engineering program management, delivery management, technical operations, or a closely related role.
  • Proven experience managing complex, multi-stage, cross-functional delivery programs against external deadlines, SLAs, or customer commitments.
  • Strong understanding of technical delivery environments involving data pipelines, software systems, AI/ML workflows, or enterprise technology.
  • Working knowledge of data pipeline concepts including throughput, batching, versioning, data quality, completeness, consistency, and duplication.
  • Experience building program-management processes and tooling from scratch rather than relying exclusively on mature frameworks.
  • Strong ability to establish operating cadences, escalation mechanisms, capacity tracking, reporting, and delivery governance.
  • Experience working with quality assurance, testing, evaluation, or human-in-the-loop workflows is highly valuable.
  • Understanding of ground-truth creation, annotation, adjudication, evaluation metrics, or data-quality processes is an advantage.
  • Excellent written and verbal communication skills with the ability to translate effectively between engineering, quality, operations, and business stakeholders.
  • Strong analytical and problem-solving skills with excellent attention to detail.
  • High degree of ownership with the ability to proactively identify risks, resolve ambiguity, and drive issues to closure.
  • Comfortable making practical decisions in situations where requirements, processes, and priorities are still evolving.
  • Strong organisational and prioritisation skills with the ability to manage multiple workstreams simultaneously.
  • Proactive mindset with a focus on process improvement, automation, efficiency, quality, and operational reliability.
  • Comfortable working in an early-stage, high-growth environment where building scalable processes is part of the role.
  • Strong interest in AI, enterprise data, technical operations, and reliable large-scale delivery systems.
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