Staff Full stack Engineer [CONSUMER]Active$170K

HelloFresh
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The opportunity

Our New Ventures team is focused on growing our global footprint by launching our core products in new markets and expanding across multiple brands and verticals. We’re a globally distributed team operating across 7+ brands in 15+ countries, building desirable products and…

What you'll do

  • Lead the design and delivery of scalable backend platforms and distributed: systems, leveraging AI-assisted and agentic engineering workflows to accelerate delivery and improve system quality.

  • Drive technical discovery, requirements refinement, and solution architecture: in ambiguous problem spaces, translating product and business goals into scalable execution strategies .

  • Design and optimize AI-enabled development workflows , including spec-driven: development, agent orchestration, context management, automated verification, and quality validation.

  • Partner closely with product, platform, and engineering teams to foster a: strong product engineering mindset focused on customer value, experimentation, and measurable outcomes.

  • Lead architectural discussions, mentor engineers in modern backend and: AI-assisted engineering practices, and establish standards for observability, quality engineering, and system reliability.

  • Evaluate emerging technologies and AI tooling to continuously enhance: engineering effectiveness, software quality, and organizational scalability while ensuring strong human oversight and operational accountability.

What they're looking for

  • Strong experience with microservice architectures, event-driven systems (e.g.: Kafka, RabbitMQ), and distributed systems design patterns.
  • Hands-on experience with Docker, Kubernetes, and modern CI/CD practices in production environments.
  • Proficiency with relational and document databases, including PostgreSQL, MySQL, and/or MongoDB.
  • AI proficiency and advocacy . Hands-on experience leveraging AI technologies: through AI-assisted engineering workflows, LLM integrations, agentic development patterns, or ML-driven product capabilities to improve engineering velocity and product outcomes.