Senior Technical Program Manager

BCapital GmbH; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

BCapital GmbH, via a stealth-mode affiliate, seeks a Sr. Technical Program Manager to lead the Singapore engineering site and translate roadmap priorities into executable plans.

You will report to senior leaders in Dublin and New York and coordinate with the Head of Solutions & GTM in New York while driving delivery cadence on cloud and AI-powered features.

Qualifications

• 8-10+ years leading or managing software engineering teams with AI-powered or AI-adjacent products.
• Hands-on knowledge of cloud infrastructure (AWS and Azure) sufficient to plan and de-risk work.

Responsibilities

• Own the delivery cadence for the Singapore engineering team (sprint planning, standups, retros, roadmap tracking).
• Plan and sequence technical work across cloud infra, data pipelines and AI-powered features.
• Manage cross-site dependencies between Singapore, Dublin and New York.
• Run technical risk management and elevate blockers before deadlines.
• Interface with engineering leadership and CEO with honest progress updates.
• Improve tooling, processes and definition of done to ship reliably.

Skills

Leadership

Cloud infrastructure

Dagster

Airflow

Databases

AI systems production

FDE experience

Stakeholder comms

Asynchronous communication

Tools

Dagster

Airflow

Job description

Title: Sr. Technical Program Manager - Engineering

About the Company

A B Capital affiliate is working to fill several senior, founding-team roles across Dublin, Singapore, and New York. The affiliate is a confidential, stealth-mode AI company building decision intelligence for private capital markets. We're posting on their behalf while they remain in stealth.

The role

Our Singapore engineering team is growing fast, and growth without someone dedicated to program delivery is how good engineers end up firefighting instead of shipping. You are that person.

You lead the Singapore site. The Lead Data Architect and the Senior DevOps Engineer based here

report to you, and you report jointly to the Head of Solutions & GTM in New York and the Head of

Applied AI in Dublin.

This is not a hands‑on coding role, and it is not a role for someone who wants to go deep on model architecture or retrieval internals — we have applied AI scientists and AI engineers for that. It is a role for someone who has run software engineering teams before, knows what a healthy delivery cadence looks like, and can hold a credible technical conversation about the systems being built well enough to plan around them realistically, spot risk early, and keep multiple engineers moving in the same direction under real‑time pressure.

You will work closely with the senior engineers on the Singapore team and with the Head of Engineering in Dublin, translating roadmap priorities into a plan the team can actually execute, and translating what is actually happening on the ground back up so leadership is never surprised.

WHAT YOU WILL DO

• Own the delivery cadence for the Singapore engineering team. Sprint planning, standups, retros, roadmap tracking — the operating rhythm that turns a list of priorities into shipped software.
• Plan and sequence technical work realistically. Understand the systems well enough — cloud infrastructure, data pipelines, AI‑powered features — to break down work sensibly, estimate honestly, and know when a plan is optimistic rather than achievable.
• Manage cross‑site dependencies. Coordinate delivery between Singapore, Dublin and New York so that work blocked on another site’s output is flagged early, not discovered at the deadline.
• Run technical risk management. Identify where a dependency, a design decision, or a resourcing gap threatens a deadline, and elevate or resolve it before it becomes a fire.
• Interface with engineering leadership. Give engineering leadership and the CEO an honest, current picture of progress, risk and blockers — no surprises, no sugar‑coating.
• Improve how the team works. Tooling, process, documentation, definition of done — the unglamorous program‑management work that compounds into a team that ships reliably.

What we are looking for

REQUIRED

• 8-10+ years leading or managing software engineering teams, including direct experience leading teams building AI‑powered or AI‑adjacent products. You do not need to have built the models yourself, but you need to have run the team that developed AI applications.
• In‑depth, hands‑on‑enough working knowledge of modern cloud infrastructure — AWS and Azure — sufficient to plan and de‑risk work without needing an engineer to translate for you.
• Solid working knowledge of data orchestration and pipeline tooling (Dagster or equivalents such as Airflow), and general database technologies (relational and non‑relational), enough to understand what the team is actually building and why certain things are hard.
• General fluency in how AI systems are engineered in production — retrieval, agents, evaluation, MLOps‑style concerns — is sufficient to plan around these systems realistically and ask the right questions. Deep expertise in the underlying models or in deep learning theory is not explicitly required.
• Experience with forward‑deployed engineering (FDE) work — sitting with customers, understanding their environment and requirements directly, and translating that into a delivery plan rather than working only from a written spec.
• A genuine track record of shipping software on realistic timelines under real constraints, not just running processes for their own sake.
• Excellent stakeholder communication — you can give an honest status update to a founder or a head of engineering without spin, and you can hold a technical conversation with a senior engineer without needing translation.
• Comfort as one of the senior operational voices on the Singapore site, with engineering leadership based in Dublin. You need to be self‑directing and a genuinely good asynchronous communicator.

STRONGLY PREFERRED

• Direct experience running delivery for a small, fast‑moving engineering team (not a large, process‑heavy organization) at an early‑stage or high‑growth company.
• Familiarity with agentic AI systems, LLM tooling, or retrieval‑augmented systems specifically, even at a working rather than expert level.
• Experience with LLM‑assisted coding tools such as Claude Code and an understanding of how they change engineering workflow and planning.
• Background in financial services, investment technology, or another domain with strict permissioning and high delivery stakes.
• Formal program or project management training (e.g., PMP, Scrum/Agile certifications), though we care far more about what you have actually delivered.

NOT REQUIRED

• Deep learning, machine learning research, or AI model‑building expertise. This role plans around AI systems; it does not build them.
• Private equity experience. Interest in how investment decisions actually get made matters more.

Process

• Intro call with the hiring manager (30 min)
• Delivery deep dive — walk us through a software engineering program you ran end to end, including where it went wrong (60 min)
• Technical planning exercise: break down and sequence a realistic AI‑product delivery scenario, discussed live (60 min)
• Founder conversation and team fit (45 min)

We aim to close within three weeks of first contact.

We are an equal opportunity employer. We are building a team from a deliberately wide range of backgrounds and will make reasonable accommodations throughout the process — just tell us what you need.

This role is at a stealth‑mode company. Further details on the product and the backing are shared under NDA at the second stage.