Senior AI Engineer

Alpas AI

. Design, build and operate production AI agents with LangGraph .

Posted 10/12/2026full-timeBerlin • GermanySeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and operating production AI agents, with a strong focus on MLOps practices, including CI/CD and monitoring. Proficient in Python and familiar with agent frameworks, vector databases, and NLP model training.

Highest-signal resume keywords

MLOpsPythonLangGraphNLP Model TrainingGCP

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI EngineeringML EngineeringBackend EngineeringSoftware Engineering PracticesTestingCI/CDDockerKubernetesTerraformVector Databases

Soft Skills

Knowledge SharingCollaboration

Tools & Technologies

FastAPIPub/SubArgo

Industry Keywords

B2B Data ProductsProcurementSupply Chain

Tech Stack

Tools & technologies

CloudDockerGoogle Cloud PlatformKubernetesPythonPyTorchTerraform

About the role

Key responsibilities & impact

Design, build and operate production AI agents with LangGraph
Implement agentic workflow patterns including planning, tool use, reflection and human-in-the-loop
Build NLP and RAG pipelines using vector databases, retrieval strategies and evaluation
Integrate agents with backend services including Python, FastAPI, Pub/Sub and GCP
Keep agent-to-agent and agent-to-backend interfaces scalable
Own MLOps for agentic workloads, including CI/CD, monitoring, evaluation pipelines, cost control and inference efficiency
Set and meet quality targets, such as an under-1% failure rate for the search agent
Benchmark models and approaches
Maintain code quality through reviews and documentation
Share knowledge across the team
Own projects end to end, from design to production operation
Report directly to the CTO and work in small, cross-functional product teams

Requirements

What you’ll need

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, including testing, CI/CD, Docker and cloud; GCP preferred
Experience with LangGraph or comparable agent frameworks, vector databases and evaluation of LLM systems
Fluent English (C1)
Based in the EU and able to work hybrid from Berlin
Experience with procurement, supply chain or B2B data products
PyTorch and NLP model training
Kubernetes
Terraform
Argo

Benefits

Comp & perks

26 days of annual leave
Hybrid work environment
Nice office in Berlin, Prenzlauer Berg
Awesome team events
Inclusive company culture with a diverse team
Rapid development with a steep learning curve
Work on an AI-core product and develop cutting-edge ML models and NLP systems
High ownership and responsibility to manage your own projects
Immediate impact for stakeholders and close collaboration with the Product team
Fast-paced environment with challenging tasks
Honest, fast, and open collaboration
Subject-matter expertise valued and challenge encouraged