Senior AI Engineer (f/m/d)

Alpas · Berlin · Hybrid

• Employment typeFull-time
• Experience levelSenior
• Salary signalSalary not listed
• Last checked1 hour ago
• Source valid throughNov 11, 2026

Role Overview

About Alpas Alpas is a Y Combinator portfolio company building agentic sourcing technology for direct procurement. Our AI agents find, qualify and enrich suppliers so procurement teams reach objectives such as cost reduction, risk mitigation, resilience and innovation. We are based in Berlin, Prenzlauer Berg, and work hybrid. The role You join our Engineering team as a senior individual contributor and report directly to the CTO. We work in small, cross-functional product teams without middle management; you own your projects end to end, from design to production operation. Your mission: Enable fully-automated supplier analysis at stellar quality. Your responsibilities Design, build and operate production AI agents with LangGraph, including agentic workflow patterns (planning, tool use, reflection, human-in-the-loop) Build NLP and RAG pipelines (vector databases, retrieval strategies, evaluation) that feed the agents Integrate agents reliably with our backend services (Python, FastAPI, Pub/Sub, GCP) and keep agent-to-agent and agent-to-backend interfaces scalable Own MLOps for agentic workloads: CI/CD, monitoring, evaluation pipelines, cost control and inference efficiency Set and meet quality targets (for example under 1% failure rate for the search agent) and benchmark models and approaches Keep the codebase healthy and share knowledge across the team through reviews and documentation What we are looking for If you match most of these requirements and not all of them, you should still apply. At least 5 years of professional experience as an AI, ML, MLOps or backend engineer (working-student time does not count) Hands-on experience shipping LLM-based or agentic systems to production, not only prototypes Degree in computer science, AI or a closely related field, or equivalent practical background Strong Python and software-engineering practices (testing, CI/CD, Docker, cloud; GCP preferred) Experience with LangGraph or comparable agent frameworks, vector databases and evaluation of LLM systems Fluent English (C1); based in the EU, able to work hybrid from Berlin PyTorch and NLP model training, Kubernetes, Terraform, Argo Experience with procurement, supply chain or B2B data products Your benefits Work on an AI-core product, develop cutting-edge ML models and NLP systems for automating the supplier search that drive innovation and deliver real impact High ownership and responsibility to manage your own projects See your work deliver immediate results for stakeholders and collaborate closely with our Product team Work in a fast-paced environment with challenging tasks (zero-boredom-guarantee) Rapid development with a steep learning curve Awesome team events and an inclusive company culture with a diverse team A hybrid work environment and a nice office in Berlin, Prenzlauer Berg Honest, fast, and open collaboration as well as strong communication skills We hire you because you are the subject-matter expert in your fields, we appreciate being challenged Ability and willingness to commit to goals and tangible impact Resourceful self-starters who hold themselves to high standards, have attention to detail, are intrinsically motivated & eager to learn on a daily basis Proactive hands-on working style with passion for customer-facing tasks Team members who are excited about our mission & tech Find more English Speaking Jobs in Germany on Arbeitnow

Why It Matches

This full-time role is listed as hybrid in Berlin. The source does not expose a salary range, so confirm compensation before investing in a long application. The match score reflects role clarity, work mode, location, freshness, salary visibility, and description depth—not a promise that the employer will select a candidate.

Questions to Check Before Applying

• Does the source describe the same title, company, location, and work arrangement shown here?
• Which required skills can you prove with a result, project, metric, or certification?
• How often must you work on site, and is the commute practical for the stated schedule?
• When will the employer disclose the salary range and total compensation?

Career Guides for This Role