Principal Engineer, Growth Mega Alliance (all genders)
HelloFresh · Berlin, Berlin, Germany
What the posting says
Each fact carries its state:Statedfound in the postingConflictstwo statements disagree, both quotedNot mentionedthe posting does not say
- Employment typeStated
- Full time
- ExperienceStated
- 10+ years
Not mentioned in this posting
“Not mentioned” means the posting does not say. It is not a no. You could ask the recruiter.
- PayNot mentioned
- The posting does not say
- Work arrangementNot mentioned
- The posting does not say
- ShiftNot mentioned
- The posting does not say
- EducationNot mentioned
- The posting does not say
- Visa sponsorshipNot mentioned
- The posting does not say
Requirements, each with its sentence from the posting
These are the employer’s words. The index does not judge whether you meet them.
- AI coding agentsrequired
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.
from the posting - GenAI integration at scalerequired
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.
from the posting - Growth domain constraintsrequired
Fluent in growth domain constraints: PSP behavior, consent and privacy requirements across markets, deliverability limits, attribution windows, and incrementality measurement.
from the posting - Distributed systemsrequired
Expert in distributed systems, microservices, and event-driven patterns (Kafka).
from the posting - AWSrequired
Deep AWS experience.
from the posting - Go, Kotlin, Python, or TypeScriptrequired
Strong proficiency in Go, Kotlin, Python, or TypeScript.
from the posting - Large-scale systems design and operationrequired
Track record of designing and operating large-scale, multi-region systems.
from the posting - Experimentation design and analysisrequired
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.
from the posting - SQL and BI toolingrequired
Able to work directly with data (SQL, BI tooling) and trace the full signal chain from instrumentation to business metric.
from the posting - Written communicationrequired
Exceptional written communication — your documents make complexity smaller, not larger.
from the posting - Influence without authorityrequired
Able to influence without authority; direct, low-ego, and comfortable disagreeing with senior stakeholders while keeping the relationship intact.
from the posting - English fluencyrequired
Fluent English.
from the posting - AdTech or paid mediapreferred
Deep familiarity with at least two of: AdTech / paid media infrastructure, funnel optimization, payment orchestration, CRM and lifecycle communications, or pricing and incentive optimization.
from the posting - Multi-market subscription experiencepreferred
Experience in a multi-market subscription or e-commerce business preferred.
from the posting - Germanpreferred
German is a bonus.
from the posting
Read the full posting as the employer wrote it
The Role
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 alongside the senior and staff engineers who look to you as the technical lead.
What You'll Do
GenAI & Agentic Engineering Leadership
- 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.
Growth Platform Architecture
- 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.
Experimentation & Personalization
- 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.
Technical Strategy & Cross-Alliance Collaboration
- 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.
Mentorship & Engineering Culture
- Coach and grow Staff and Senior Engineers across all five pillars. Foster engineering excellence through rigorous design review, strong observability practice, and honest post-incident learning.
- Champion AI-native development workflows, TDD, DDD, and DevSecOps. Set the written communication standard through your design docs and architectural decision records.
What You'll Bring
GenAI & Agentic Engineering
- 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.
Growth Domain Expertise
- 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.
Technical Depth
- ~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.
Ways of Working
- 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.
What Success Looks Like
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.
Why Work With Us
- Make an Impact: GMA's platforms touch every customer HelloFresh acquires and every euro it collects. Your decisions move top-line numbers at a company that has changed the way millions of people eat.
- Real Scope: You own technical direction, make consequential architectural calls, and ship things that matter — at a scale that makes the problems genuinely hard.
- AI at the Frontier: You will have the mandate, resources, and organizational support to lead AI-native engineering transformation — not advocate for it from the sidelines.
- Direct Access: You work daily with engineering, product, and business leadership, with the visibility and accountability that implies.
- Learn & Grow: Annual learning budget, HelloFresh Academy, and internal mobility across a large, technically ambitious engineering organization.
The posting text is reproduced as the employer wrote it; the index adds nothing to it.