Head of Product Engineering
BidMachine
| Company | BidMachine |
| Category | Engineering |
| Location | Barcelona |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Director |
| Salary | Not stated by the employer |
| Posted | 13 Jul 2026 |
| Last verified | 10 Aug 2026 |
| Source | Employer ATS (greenhouse) |
Description
BidMachine Exchange – a fast-growing global programmatic exchange built for the future of in-app advertising.
BidMachine operates with a strong US foundation and an international presence, with teams across Warsaw, Barcelona, Parkland (FL), and remote experts around the world.
We combine deep AdTech expertise, proprietary technology, and a data-driven mindset to deliver transparency, performance, and efficiency in the mobile advertising ecosystem. Why BidMachine? At BidMachine, we are building more than an exchange — we are shaping the infrastructure that powers fair, efficient, and scalable in-app programmatic advertising. Our mission is to create a high-performance marketplace where publishers maximize value and advertisers access premium inventory with full transparency and control. We are proud of our technology, our ambitious vision, and our globally distributed team of talented professionals who continuously raise the bar in AdTech.
Here’s what we value, and what we hope you do too:
Ownership & Accountability We move fast, take responsibility, and think like builders. Every team member has a direct impact on product growth and market success.
Data-Informed Excellence We leverage data to make smarter decisions, optimize performance, and build scalable solutions that deliver measurable results.
Innovation & Technical Depth We solve complex programmatic challenges with cutting-edge technology and a deep understanding of the ecosystem.
Global Collaboration We work across cultures, time zones, and disciplines — united by shared goals and high standards.
Ambition & Impact We are here to build something significant — a best-in-class exchange that competes with the strongest players in the market. BidMachine's UA business unit is looking for an experienced Head of Product Engineering to own the technical and product vision of our demand-side platform (DSP) — the engine that runs managed-service campaigns for advertisers today, with a self-service version on our roadmap.
You will unify Data Science, Data Engineering, Data Analytics, BI, and our bidding/prediction stack into a single, coherent product, replacing today's fragmented workflow with one clear roadmap and one set of aligned decisions. This is a hands-on leadership role: you'll sit above our Data Science function, work daily with our go-to-market and sales leadership, and carry direct influence over how we compete with the handful of full-stack players (exchange + mediation + DSP) in this industry.
Location: Barcelona, Spain
Responsibilities:
Own the end-to-end technical and product roadmap for the UA DSP, from bidding and prediction through to reporting and BI.
Unify Data Science, Data Engineering, Data Analytics, BI, and backend engineering (predictor/bidder) into one product function with consistent, aligned decision-making.
Lead, grow, and mentor a team of roughly 20 across engineering, data science, and analytics; accelerate the growth of the existing Data Science function.
Partner closely with the Go-to-Market/Revenue lead and Head of Sales to translate market opportunities into technical feasibility assessments and vice versa.
Drive the long-term transition from managed-service to self-service tooling for advertisers.
Bring engineering rigor and a genuine product mindset — at BidMachine, "product" means engineers who understand the business and can set direction, not a separate function.
Move quickly from close collaboration on direction-setting to independently owning and defending product strategy.
Requirements:
10+ years of experience in software engineering, with demonstrated hands-on experience having built and scaled a DSP or comparable real-time bidding platform.
5+ years in a senior engineering or product engineering leadership role, managing teams of 15–20+ across multiple disciplines.
Strong working knowledge of machine learning and data sc