About The Position
We are looking for a Staff Fullstack Engineer to take on technical leadership and end-to-end ownership for a new, customer-facing Agentic Product at happyhotel. The focus is on measurable impact, combining strong product sense with hands-on engineering to build reliable, secure, and scalable agentic systems. This role does not involve disciplinary personnel responsibility; leadership is exercised through expertise, standards, and ownership.
Requirements
- Product Shipper: Proven track record of successfully releasing customer-facing products end-to-end (UX + Backend + Ops).
- Fullstack Pro: Deep technical expertise in our stack (TypeScript + Angular).
- Product Mindset: Balance technical excellence with business outcomes and make pragmatic decisions for the product.
- Production Experience: Proficient with AWS, Docker, CI/CD, and a strong reliability mindset.
- Agentic Know-how: Hands-on experience with agentic coding or workflows (LLMs that plan and use tools).
- Collaboration: Work reliably, pragmatically, and with a strong team orientation across all functions.
- Languages: Communicate clearly in German and English.
Nice To Haves
- AI Track Record: Experience guiding AI products from MVP to broad adoption in production.
- Messaging & Data: Experience with Pub-Sub systems (RabbitMQ, SQS) and MongoDB performance and data modeling.
Responsibilities
- Fullstack-Execution: Develop UI and backend services in our stack (TypeScript/Angular), building robust APIs and integrations.
- Outcome Focus: Take responsibility for measurable results, defining success metrics, baselines, and guardrails. Impact is valued over output.
- AI Strategy: Collaborate closely with Product to identify high-leverage workflows for automation using intelligent agents.
- Iterative Shipping: Translate ambiguous problems into iterative releases (MVP → v1 → Scale), making smart trade-offs between UX, risk, and engineering quality.
- Agentic Architectures: Design and implement architectures for AI agents, covering tool use, orchestration, and cost/latency control.
- Robust Evaluation: Establish test sets and regression suites to ensure the quality, safety, and reliability of AI features in production.
- Engineering Standards: Set benchmarks for testing, code quality, CI/CD, and scalability in a cloud environment (AWS).
- Tech Leadership: Elevate the team's level through design reviews and pairing, providing direction and setting standards for AI reliability.
- Mentoring & Hiring: Support team growth through mentoring and actively participate in the interview process.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
