Overview
About the Role This is a hands-on AI engineering role at a fast-growing, Y Combinator-backed B2B SaaS startup building AI-powered sales automation for distributors and manufacturers. You will work across the full stack to design and ship end-to-end AI systems that directly drive product growth and customer impact. What You'll Do Build, deploy, and optimize AI agents end-to-end across the full stack. Work with embeddings and fine-tune LLMs for classification and reranking tasks. Optimize algorithms for product search and discovery. Apply RLHF and DPO techniques to align LLMs with human feedback. Build data pipelines to process large-scale unstructured data efficiently. Improve backend scalability, stability, and performance. What We're Looking For 2+ years of engineering experience, with substantive AI/LLM or backend-oriented depth (not frontend-focused). Strong experience with NLP, LLMs,
Full job description
Full Job Description
About the Role
This is a hands-on AI engineering role at a fast-growing, Y Combinator-backed B2B SaaS startup building AI-powered sales automation for distributors and manufacturers. You will work across the full stack to design and ship end-to-end AI systems that directly drive product growth and customer impact.
What You'll Do
-
Build, deploy, and optimize AI agents end-to-end across the full stack.
-
Work with embeddings and fine-tune LLMs for classification and reranking tasks.
-
Optimize algorithms for product search and discovery.
-
Apply RLHF and DPO techniques to align LLMs with human feedback.
-
Build data pipelines to process large-scale unstructured data efficiently.
-
Improve backend scalability, stability, and performance.
What We're Looking For
-
2+ years of engineering experience, with substantive AI/LLM or backend-oriented depth (not frontend-focused).
-
Strong experience with NLP, LLMs, embeddings, ML, and AI-powered applications.
-
Demonstrated experience building and scaling data and ML pipelines, including large-scale unstructured data.
-
Hands-on experience applying RLHF or DPO to align LLMs with human feedback.
-
Full-stack development skills using React, TypeScript, and Next.js.
-
Experience with containerization (Docker, Kubernetes), cloud infrastructure (AWS, Azure, or GCP), and infrastructure as code (Terraform).
-
Strong computer science fundamentals.
-
Ability and willingness to work on-site in Munich on a regular basis.
Compensation & Benefits
Salary range: 80,000 to 130,000 EUR annually. Visa sponsorship is available.
Location
On-site in Munich, Bavaria, Germany. This is not a remote or heavily hybrid position; regular in-person presence is expected.
Tips for this job
Practical Job and Scholarship guidance. These tips do not replace official rules or create new eligibility requirements.
- Tailor the CV and application to the responsibilities and required skills stated on the official employer page.
- Use concrete evidence of relevant work, projects and measurable results rather than generic claims.
- Confirm location, work authorization, remote restrictions and sponsorship terms before applying.
- Apply through the original employer or official recruitment destination shown on this page.
Verification notes
Discovered directly from the employer’s public Ashby Job Postings API. The complete public role content and compensation metadata were normalized into safe candidate-facing sections.
Job and Scholarship is the discovery and verification layer. Confirm eligibility, dates, salary/funding and application instructions on the original source before submitting anything.
Clera (ashby) ↗Browse current Job and Scholarship listings from Clera (ashby) →
