Principal Engineer, Growth Mega Alliance

About the Role

The Growth Mega Alliance (GMA) is responsible for building platforms that enable HelloFresh to acquire, convert, and retain customers in 18 markets through multiple brands. These platforms span five key areas: AdTech, Conversions, Payments, Communications, and Customer Value Optimization (CVO). As the Principal Engineer, you will serve as the technical visionary guiding architecture across these pillars, leading critical cross-functional initiatives, and elevating the technical standards throughout the organization. This hands-on leadership role involves active coding, design, and code review alongside senior and staff engineers who look to you for technical leadership.

Primary Responsibilities

• Lead GMA's strategy for Generative AI (GenAI), pinpointing the highest-impact uses of AI/ML across all pillars to enhance engineering efficiency and customer capabilities.
• Develop and scale agentic engineering workflows where AI-driven code generation is specification-led, establishing frameworks and guardrails enabling squads to work efficiently with AI-assisted tools.
• Define how engineering teams must evolve in skills, processes, and culture to maximize benefits from AI-native development tools.
• Oversee long-term architecture for GMA’s five pillars, including real-time personalization, large-scale experimentation, AI/ML automation, and data consistency across domains.
• Lead complex architectural decisions involving shared identity schemas, experimentation assignments, signal integration between AdTech and Conversions, and payment authorization flows, ensuring smooth and impactful migrations.
• Guarantee integration of GMA platforms with internal infrastructure, meeting global-scale requirements for reliability, latency, and observability.
• Define a scalable experimentation framework to optimize decision-making based on experimental data, managing the full data flow from event tracking to business metrics including instrumentation standards, identity resolution, attribution timing, and signal fidelity.
• Set and communicate GMA’s long-term technical vision clearly for both engineering teams and executive leadership, participating in company-wide architectural efforts to foster shared standards and prevent fragmentation.
• Mentor and develop staff and senior engineers in all pillars, promoting engineering excellence through code reviews, observability best practices, and constructive incident retrospectives.
• Promote AI-native workflows, test-driven development (TDD), domain-driven design (DDD), and DevSecOps, and lead by example with well-crafted design documentation and architectural decision records.

Required Qualifications and Experience

• Demonstrable hands-on experience deploying AI coding assistants (such as Claude Code, Cursor, GitHub Copilot, or OpenCode) in production or near-production settings, beyond experimental use.
• Proven experience integrating Generative AI into customer-facing offerings or internal business functions at scale, with informed insight into the organizational changes needed to harness productivity gains from AI.
• Comprehensive expertise in at least two of the following domains: AdTech and paid media infrastructure, funnel optimization, payment orchestration, CRM and lifecycle communications, or pricing and incentive optimization.
• Understanding of domain-specific constraints including payment service provider behaviors, market-wise consent and privacy regulations, deliverability limits, attribution time-frames, and incrementality measurement. Prior experience in multi-market subscription or e-commerce businesses is preferred.
• Approximately 10+ years of software engineering experience, including at least 5 years at principal engineering level within a high-growth, cloud-native context.
• Technical mastery of distributed systems, microservices architecture, and event-driven frameworks such as Kafka; strong command of AWS cloud services; proficiency in at least one of Go, Kotlin, Python, or TypeScript.
• A successful history designing and operating scalable, multi-region systems, with comfort in conducting hands-on architecture reviews and addressing critical system bottlenecks.
• Familiarity with experimentation design and analytic approaches; ability to engage directly with data analysis tools like SQL and BI software, tracing data flows from instrumentation to business outcomes.
• Exceptional written communication skills that simplify complex technical details for various audiences.
• Strong influencing ability without formal authority, capable of candid but respectful discussions with senior leadership to maintain positive relationships.
• Fluent English language skills; German proficiency is advantageous.

Success Metrics

• Within 3 months: Thoroughly map GMA’s critical architectural dependencies, identify GenAI application opportunities, conduct design reviews across multiple pillars, and establish a prioritized set of architectural bets for the year.
• Within 6 months: Architectural guidance is reflected in roadmaps; AI-native workflows have been deployed in production; at least one significant cross-pillar project is underway with clear measurement instrumentation.
• Within 12 months: Platforms exhibit improved scalability, observability, and AI capability; engineering standards are formalized and followed; you become the go-to technical leader for the company’s most challenging growth engineering issues.

Why Join Us?

• Your work impacts every customer acquisition and revenue touchpoint for HelloFresh, with decisions influencing the company’s top-line growth.
• You will drive important architectural decisions and lead initiatives at scale, tackling technically complex challenges.
• You will spearhead AI-native engineering transformation with full organizational support, not merely advocate from the sidelines.
• You will engage daily with cross-functional leadership, gaining visibility and high accountability.
• Access to continuous learning opportunities, including an annual education budget, internal academy, and mobility within a large technical organization.