About the Job
The Growth Mega Alliance (GMA) builds the platforms that power how HelloFresh acquires, converts, and retains customers across 18 markets and multiple brands, across five pillars: AdTech, Conversions, Payments, Communications, and Customer Value Optimization (CVO).
As Principal Engineer, you are the technical visionary for these platforms. You define architectural direction across all five pillars, lead the most consequential cross-cutting initiatives, and raise the technical bar for the entire organization. This is a hands-on leadership role - you code, review, and design alo...
Key Responsibilities
Own GMA's GenAI strategy: identify the highest-leverage opportunities across all five pillars where AI/ML unlocks step-change outcomes, for both engineering productivity and customer-facing capabilities.
Establish agentic development workflows — where specs drive AI-assisted code generation — and scale them from early adopters to standard practice. Build the guardrails and reference architectures that enable squads to work AI-natively.
Develop and articulate a clear point of view on how engineering teams need to evolve in skills, process, and culture to realize the gains that agentic tools make possible.
Own the long-term technical architecture across GMA's five pillars: real-time personalization, experimentation at scale, AI/ML-driven automation, and cross-pillar data integrity.
Lead the most complex architectural decisions (shared identity schemas, experiment assignment, AdTech-to-Conversions signal loops, payment authorization flows) and drive migrations with large impact.
Ensure GMA platforms integrate cleanly with internal infrastructure and meet reliability, latency, and observability requirements at a global scale.
Define GMA's experimentation strategy and execution framework to optimize experimentation-based decision-making at scale.
Own the data path from customer event to business decision: instrumentation standards, identity resolution, attribution windows, and signal quality.
Define GMA's multi-year technical vision and communicate it with the precision engineers need and the clarity executives can act on. Represent GMA in company-wide programs.
Partner with Intelligent Platforms, Consumer, and Operations Mega Alliances to drive shared architectural standards and prevent fragmentation.
Required Skills & Abilities
Practical, hands-on experience with AI coding agents (e.g., Claude Code, Cursor, GitHub Copilot, OpenCode) in production or near-production environments — not just experimentation.
Experience integrating GenAI into customer-facing products or internal business processes at scale, with a clear point of view on the team and cultural changes required to realize the productivity gains.
Deep familiarity with at least two of: AdTech / paid media infrastructure, funnel optimization, payment orchestration, CRM and lifecycle communications, or pricing and incentive optimization.
Fluent in growth domain constraints: PSP behavior, consent and privacy requirements across markets, deliverability limits, attribution windows, and incrementality measurement. Experience in a multi-market subscription or e-commerce business preferred.
~10+ years in software engineering, with ~5+ years at principal level in a high-growth, cloud-native environment.
Expert in distributed systems, microservices, and event-driven patterns (Kafka). Deep AWS experience. Strong proficiency in Go, Kotlin, Python, or TypeScript.
Track record of designing and operating large-scale, multi-region systems. Comfortable doing hands-on architectural reviews and solving critical bottlenecks directly.
Working knowledge of experimentation design and analysis; able to work directly with data (SQL, BI tooling) and trace the full signal chain from instrumentation to business metric.
Exceptional written communication — your documents make complexity smaller, not larger.
Able to influence without authority; direct, low-ego, and comfortable disagreeing with senior stakeholders while keeping the relationship intact.
Fluent English. German is a bonus.
3 months — You have mapped GMA's critical architectural dependencies and GenAI opportunities, conducted design reviews across multiple pillars, and established a point of view on the highest-leverage technical bets for the year.
6 months — Your architectural direction is reflected in roadmaps. GMA's first AI-native workflows are in production. At least one cross-pillar initiative is running under your technical ownership with clear instrumentation.
12 months — GMA's platforms are measurably more scalable, observable, and AI-capable. Engineering standards are set and followed. You are the person leaders across HelloTech bring their hardest growth-engineering problems to.
