Senior AI Engineer – Location AI

Jobtailor; Deutschland; Remote; EUR 110.000 - 170.000; Vollzeit

Zusammenfassung

Jobtailor seeks an experienced software engineer to define product behavior, evaluation frameworks, and data pipelines for non-deterministic AI products. You will own MVP delivery against a technical design, balancing quality and usefulness for end users.

Responsibilities include evaluating APIs/SDKs, identifying misuses, and implementing fixes, with strong Python or TypeScript and on-call readiness required.

Qualifikationen

• Bachelor's degree in a STEM field.
• 5+ years of software engineering with production ownership of services, pipelines, or SDKs.
• 2+ years shipping LLM-backed features to real users in systems with error budgets and on-call rotations.
• Experience designing evaluations for non-deterministic systems.
• Data engineering depth, including SQL and at least one distributed processing framework.
• Fluency with Python or TypeScript and reading code in other languages.
• Willingness to participate in on-call rotation, including outside hours.

Aufgaben

• Define product behavior, measurement frameworks, evaluation systems, datasets, and regression gates for non-deterministic AI products.
• Continuously evaluate APIs, SDKs, data representations, and reference applications from end-user perspectives.
• Identify misuse, integration anti-patterns, and product gaps; recommend and implement fixes.
• Own MVP delivery against a technical design while balancing quality and useful increments.
• Build data pipelines and tooling for ingestion, conflation, entity resolution, quality checks, and batch/streaming processing.
• Track and evaluate external datasets, models, benchmarks, research, and open-source releases.
• Design feedback loops and instrumentation that provide reproducible failure context.
• Design model-tool boundaries and build or improve model harnesses.
• Optimize request latency and cost through streaming, partial results, caching, model routing, and prompt structure.
• Build internal CLI, MCP, and other engineering tools and share reusable components.
• Conduct code and design reviews and mentor engineers on evaluation practices.
• Investigate unresolved technical questions in AI systems.
• Participate in a 24/7 on-call rotation to maintain system availability.

Kenntnisse

Python

TypeScript

Data Engineering

Distributed processing

SQL

APIs & SDKs

On-call readiness

Clear written communication

Mentoring engineers

Ausbildung

Bachelor's Degree in STEM

Tools

MCP

Agent Orchestration

CLI Tools

Open-Source Releases

Reference Applications

Jobbeschreibung

• Define product behavior, measurement frameworks, evaluation systems, datasets, and regression gates for non-deterministic AI products
• Continuously evaluate APIs, SDKs, data representations, and reference applications from end-user perspectives
• Identify misuse, integration anti-patterns, and product gaps; recommend and implement fixes
• Own MVP delivery against a technical design while balancing quality and useful increments
• Build data pipelines and tooling for ingestion, conflation, entity resolution, quality checks, and batch/streaming processing
• Track and evaluate external datasets, models, benchmarks, research, and open-source releases
• Design feedback loops and instrumentation that provide reproducible failure context
• Design model-tool boundaries and build or improve model harnesses
• Optimize request latency and cost through streaming, partial results, caching, model routing, and prompt structure
• Build internal CLI, MCP, and other engineering tools and share reusable components
• Conduct code and design reviews and mentor engineers on evaluation practices
• Investigate unresolved technical questions in AI systems
• Participate in a 24/7 on-call rotation to maintain system availability

Requirements

• Bachelors degree in a STEM discipline
• 5+ years of software engineering experience with production ownership of services, pipelines, or SDKs
• 2+ years shipping LLM-backed features to real users in systems with error budgets, on-call rotations, and customer-facing regressions
• Direct experience or deep understanding of designing evaluations for non-deterministic systems
• Experience building datasets and identifying failures caught by evaluation
• Data engineering depth, including SQL and at least one distributed processing framework
• Experience with pipelines where data correctness is critical
• Fluency with tool calling and agent orchestration, including stale context, hallucinated arguments, silent partial success, and unbounded loops
• Working knowledge of more than one agent harness
• Strong Python or TypeScript skills and ability to read code in other languages
• Experience diagnosing latency in distributed request paths
• Clear written communication
• Ability to participate in an on-call rotation, including immediate response outside normal working hours and weekends
• Nice to have: geospatial data experience, public API or SDK design, MCP or similar tool transports, CI evaluations, automotive/IVI/CarPlay/Android Auto, voice pipelines, constrained or offline compute, and first external integrations

Core Competencies

Demonstrates expertise in building and optimizing data pipelines, designing evaluation frameworks for non-deterministic AI systems, and delivering MVPs with a focus on quality and user experience. Proficient in Python or TypeScript, with a strong understanding of distributed processing and data correctness.

Highest-signal resume keywords

• Data Engineering Depth
• Python or TypeScript Skills
• Experience with Non-Deterministic Systems
• Building and Optimizing Data Pipelines
• On-Call Rotation Participation

Hard Skills

• Software Engineering
• Data Pipeline Development
• SQL
• Distributed Processing Frameworks
• Evaluation Design
• Latency Diagnosis
• MVP Delivery
• Model Harness Design
• APIs and SDKs
• Data Quality Checks

Soft Skills

• Clear Written Communication
• Mentoring Engineers

Certifications & Qualifications

• Bachelor's Degree in STEM

Industry Keywords

• Non-Deterministic AI
• LLM-Backed Features
• Geospatial Data
• Automotive/IVI
• Voice Pipelines

Tools & Technologies

• CLI Tools
• MCP
• Agent Orchestration
• Open-Source Releases
• Reference Applications