Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on Oct 15, 2026. HelloFresh scores A on the Alion truth index.
The role and the team
You'll join HelloFresh's GenAI Enablement Squad, a cross-functional team helping teams across the company unlock the practical value of AI. Our mission is simple: identify high-impact problems, build AI-powered solutions that solve them, and scale what works.
As a Senior Forward Deployed Engineer, you'll work directly with engineering teams and business functions to understand their workflows, identify high-value opportunities, and build AI-powered solutions that solve real operational problems. You'll act as the bridge between users and technology-embedding with teams, rapidly iterating on prototypes, and turning successful ideas into production systems.
This is a highly hands-on engineering role. You'll own projects from discovery through deployment, collaborating closely with product managers, engineers, and non-technical stakeholders. You'll thrive in ambiguous environments, moving quickly to validate ideas while maintaining the engineering quality required for production.
You'll join a team that values pragmatism over hype. We use the best tool for the problem-not the newest one-and measure success by the impact our solutions create.
What you'll do
- Partner directly with engineering and business teams across HelloFresh to understand their workflows and identify opportunities where AI can create measurable value.
- Embed with teams to rapidly prototype AI-powered solutions, gather feedback, and iterate based on real user needs.
- Design, build, deploy, and operate production-grade AI applications, including agents, workflow automations, retrieval systems, and internal tools.
- Build role-specific AI assistants distributed through our internal plugin marketplace, enabling teams to automate repetitive work and improve productivity.
- Work across the full lifecycle of AI solutions-from discovery and experimentation to production deployment and continuous improvement.
- Balance speed with engineering quality, ensuring solutions are reliable, observable, secure, and cost-effective.
- Collaborate closely with platform engineers to leverage and improve shared AI infrastructure where appropriate.
- Share learnings and reusable patterns that help accelerate future AI initiatives across the organization.
- Mentor teammates through collaboration, code reviews, and technical discussions.
What you'll bring
- Experience building and shipping production AI applications using modern LLMs, including agents, RAG, workflow automation, structured generation, and LLM evaluation.
- Strong software engineering skills with experience designing and operating production systems.
- Experience working directly with customers or business stakeholders to translate ambiguous problems into practical software solutions.
- A product mindset with a focus on delivering measurable user and business impact.
- Ability to rapidly prototype ideas while knowing when to invest in scalability, reliability, and long-term maintainability.
- Experience with managed AI platforms such as AWS Bedrock, OpenAI, Anthropic, or Google Vertex AI.
- Strong programming skills in Python or another modern programming language.
- Excellent communication skills and the ability to collaborate effectively across technical and non-technical audiences.
- Curiosity, pragmatism, and a bias toward action.
Nice to have
- Experience building internal developer tools or productivity platforms.
- Experience evaluating AI systems for quality, latency, and cost.
- Familiarity with agent frameworks, MCP, tool calling, or workflow orchestration.
- Experience deploying AI solutions in enterprise environments.
- Experience measuring adoption and business impact of AI products.

