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WHO YOU'LL WORK WITH

You'll join our Enterprise Technology team, part of Bain's digital capabilities practice. In this multidisciplinary group, you'll help clients modernize their tech strategy, architecture, and systems -- aligning technology with business goals to drive efficiency, agility, and innovation. You'll develop enterprise-wide solutions, optimize cloud and data architectures, and integrate AI to enable scalable end-to-end digital transformations.

WHERE YOU'LL FIT WITHIN THE TEAM

Bain & Company is expanding its Technology Delivery capability across Asia Pacific (APAC) to support complex, large-scale technology transformations for leading global organizations.

We are seeking experienced Technical Program Managers and Technology Delivery leaders to lead cross-functional technical programs end-to-end, orchestrate multi-team SDLC and delivery models, and ensure system-level architectural integrity and engineering coherence.

This role sits at the intersection of strategy and engineering. You will partner closely with product, architecture, and engineering teams to translate enterprise ambition into durable business outcomes.

This role is open across our Southeast Asia and India offices.

WHAT YOU'LL DO

1) Lead cross-functional technical programs end-to-end

Lead complex programs from inception through production and sustained operations. Drive execution strategy, sequencing, and measurable outcomes across multiple engineering teams and stakeholders.
Serve as the single-threaded owner for system-level delivery health. Surface constraints early, make trade-offs explicit, and resolve risks that affect scope, quality, or launch readiness.
Define and operationalize execution mechanisms such as planning cadences, dependency tracking, release models, and risk thresholds to enable aligned decision-making at scale.
Own cross-team risk, dependency, and critical-path management. Actively unblock teams, resolve integration friction, and prevent silent failure modes in multi-system environments.
Operate metrics-first. Establish leading and lagging indicators for delivery health, including throughput, quality, NFR adherence, and release stability. Use data to improve engineering velocity and long-term system resilience.

2) Orchestrate multi-team SDLC and delivery models

Design and evolve fit-for-purpose governance that supports fast, aligned decisions across sponsor, program, and engineering levels while preserving system-level coherence.
Structure and scale multi-team delivery models such as release trains, platform-stream alignment, and dependency governance based on architectural complexity and client maturity.
Orchestrate multi-team SDLC in complex enterprise environments, including parallel agile and legacy cadences. Ensure integration sequencing, release predictability, and execution discipline.
Establish and enforce delivery guardrails across requirements quality, technical design readiness, CI/CD rigor, testing strategy, and production readiness.
Own release orchestration and go/no-go accountability. Ensure readiness across code, infrastructure, observability, rollback, operational support, and executive risk alignment.
Drive testing and validation rigor, both functional and non-functional. Embed measurable quality gates and prevent late-stage integration failures.

3) Ensure system-level architectural integrity and engineering coherence

Apply systems thinking to maintain architectural integrity across services, platforms, and domains as programs scale.
Make system-level trade-offs explicit across business, product, and engineering constraints, such as time-to-market versus resilience or autonomy versus reuse.
Institutionalize architecture and product decision quality using lightweight, traceable mechanisms such as ADRs and PDRs.
Partner closely with architecture and engineering leads to ensure architectural intent is deliverable, scalable, and operationally sustainable.
Own cross-domain dependency mapping and integration readiness. Identify systemic risks across legacy systems, shared services, vendor components, and platform layers.
Operationalize NFRs, including performance, availability, resilience, security, and observability as measurable system commitments. Ensure they are embedded into backlogs, CI/CD pipelines, release criteria, and production monitoring.
Protect long-term system health by managing technical debt visibility, capacity erosion risks, and architectural drift.

4) Embed modern AI/GenAI practices into delivery

Integrate AI-enabled delivery workflows across the SDLC, including analysis, documentation, code workflows, reviews, and quality processes, while maintaining engineering standards and accountability.
Introduce agentic and multi-step AI workflows responsibly, with clear guardrails, limits, and validation.
Lead LLMOps readiness for GenAI-enabled systems, including evaluation baselines, regression testing, drift monitoring, incident response mechanisms, and controlled model or prompt rollout.
Ensure GenAI features meet enterprise standards for reliability, observability, data protection, and risk governance before release.
Coordinate cross-functional AI dependencies across data, security, legal, infrastructure, and engineering to support responsible production adoption.

5) Lead blended teams in a client advisory environment

Operate as a senior technical delivery leader across Bain, client, and partner teams in matrixed environments while maintaining engineering credibility.
Translate system-level technical constraints into executive-ready trade-offs and decisions, aligning C-level priorities with engineering realities.
Build durable delivery capability within client organizations by raising the bar on engineering rigor, transparency, and execution discipline.

ABOUT YOU

7–12+ years of experience in technical program management or large-scale technology delivery within complex product, platform, or enterprise environments (industry, consulting, or a blend).
Demonstrated ownership of cross-team, multi-system programs with measurable delivery and system-level outcomes.
Strong technical depth. Comfortable operating with engineers on distributed systems, APIs, reliability targets (SLOs/SLIs), CI/CD, DevOps, and platform architecture.
Proven ability to serve as a single-threaded owner for system-level delivery health, driving critical-path alignment and resolving cross-team integration risks.
Experience embedding non-functional rigor (performance, scalability, resilience, security) into execution mechanisms and release readiness.
Ability to influence senior technology leaders and executives without formal authority, translating technical constraints into clear, actionable trade-offs.
Systems-level thinking, including the ability to structure ambiguity, manage dependencies, and balance feature velocity with long-term system health.
Familiarity with modern AI-enabled engineering workflows and the operational implications of LLMOps and AI risk governance.

WHY BAIN

Work on enterprise-scale, mission-critical technology transformations across industries.
Operate at the intersection of Board/C-level strategy and deep engineering execution.
Solve high-complexity, cross-domain problems that span architecture, data, platform, AI, and operating model transformation.
Build and shape a rapidly scaling Technology Delivery capability in APAC and influence how system-level delivery is defined within Bain and with our clients.
Collaborate with senior consulting leaders, architects, product leaders, and engineers in a high-performance, intellectually rigorous environment.

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