[TECH] Senior GenAI Engineer [INTELIGENT PLATFORMS]

HelloFresh; Warszawa; On-site; PLN 270,000 - 370,000; Full time

Job summary

HelloFresh in Warsaw is seeking a Senior Forward Deployed Engineer to join the GenAI Enablement Squad. You’ll work with engineering and business teams to identify AI opportunities, prototype AI-powered solutions, and deliver production-grade applications that solve real operational problems.

You’ll own projects from discovery through deployment, collaborating with product managers, engineers, and non‑technical stakeholders.

Qualifications

• Experience building and shipping production AI applications using modern LLMs, including agents and workflow automation.
• 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.

Responsibilities

• Partner directly with engineering and business teams across HelloFresh to understand workflows and identify AI value opportunities.
• Embed with teams to rapidly prototype AI-powered solutions, gather feedback, and iterate based on 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 to automate repetitive work.
• Work across the full lifecycle of AI solutions—from discovery to production deployment and continuous improvement.
• Balance speed with engineering quality, ensuring reliable, observable, secure, and cost‑effective solutions.
• Collaborate with platform engineers to leverage and improve shared AI infrastructure.
• Share learnings and reusable patterns to accelerate future AI initiatives.

Skills

AI systems

Python

LLM work

Production deployment

Stakeholder collaboration

Tools

AWS Bedrock

OpenAI

Anthropic

Vertex AI

Job description

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.