Principal Architect

Jobtailor; Deutschland; Remote; EUR 90.000 - 130.000; Vollzeit

Zusammenfassung

Jobtailor is seeking a backend AI systems engineer to design, build and operate production APIs, large-scale batch workflows, and evaluation frameworks. You will work across OpenSearch/Elasticsearch ecosystems, LLM/ML tooling, and non-deterministic components to deliver reliable enterprise solutions.

You will own end-to-end product experience, drive reliability and observability, and collaborate across stacks including frontend JS/TS where needed.

Qualifikationen

• 7+ years programming in Java, Golang, Python, or JavaScript.
• 2+ years architecting search/information retrieval systems at scale.
• 6 months to 1 year building agentic products or solutions.
• Experience with multiple modern agent frameworks preferred.
• 1+ year evaluating AI systems for quality and safety at scale.
• 5+ years shipping production software in enterprise/consumer environments.
• OpenSearch or Elasticsearch experience preferred.

Kenntnisse

Java

Golang

Python

JavaScript

RESTful APIs

Asynchronous Workflows

Statistical Concepts

Batch Workflows

Agentic Products

Digital Production Operations

Foundation Models

OpenSearch

Elasticsearch

FFmpeg

OpenCV

Tools

OpenSearch

Elasticsearch

FFmpeg

OpenCV

Agile Methodologies

Jobbeschreibung

• Experience building agentic harnesses from scratch, including capabilities such as tool use, multi-step chaining, reasoning, streaming, skills, multimodal integration, RAG, sandboxing, and state management.
• Experience designing, building, and operating production APIs and services, including RESTful APIs, streaming APIs, asynchronous workflows, service boundaries, versioning, authentication/authorization, error handling, and backward compatibility.
• Strong judgment around when to use synchronous APIs, event-driven architectures, queues, background jobs, or streaming protocols based on latency, reliability, scalability, and user experience requirements.
• Demonstrated ownership of production systems, including process improvements, roadmap contributions, defect resolution, uptime and availability monitoring, and operational reliability.
• Strong backend engineering fundamentals, with comfort working across service design, APIs, batch workflows, orchestration, observability, and production support.
• Familiarity with evaluation techniques such as creating and maintaining evaluation datasets, running offline regression evals, monitoring online production performance, rubric-based scoring, self-verification, human-in-the-loop review, AI-as-judge methods, and quality/reliability analysis at scale.
• Clear understanding of foundational machine learning and statistical concepts, including sampling, statistical significance, overfitting/underfitting, precision and recall, and quality tradeoff analysis.
• Experience building and orchestrating large-scale batch workflows that use foundation models, including LLMs and VLMs, as well as pretrained open-source models and deep learning models.
• Ability to design systems that safely and reliably automate meaningful enterprise workflows using non-deterministic AI components.
• Strong judgment around reliability, failure handling, observability, human review, and operational safety.
• Deep understanding of how to make systematic tradeoffs between quality, reliability, latency, cost, explainability, and user experience in complex AI systems.
• Ability to design pragmatic architectures that balance innovation with production readiness.
• Comfort working in environments where model behavior is non-deterministic and system design must account for uncertainty, evaluation, monitoring, and graceful failure.
• Experience with both lexical and embedding-based search methods.
• Ability to reason about relevance, ranking, latency, recall, precision, indexing strategy, and retrieval performance.
• Experience working with foundation models and open-source LLMs beyond simple API calls.
• Familiarity with lower-level model behaviors and controls, including temperature, top-p sampling, logprobs, confidence scoring, prompting strategies, and model selection tradeoffs.
• Comfort and willingness to build front-end experiences using JavaScript/TypeScript and frameworks such as React.
• While the role is primarily backend and AI systems focused, the ability to contribute to user-facing product experiences is important.
• Willingness to work across the stack and own the end-to-end product experience is essential.
• Familiarity with tools such as FFmpeg, OpenCV, or similar media-processing libraries is a plus.

Requirements

• 7+ years of a programming languages such as Java, Golang, Python, JavaScript
• 2+ years of experience architecting, designing, and optimizing search and information retrieval systems at scale.
• 6 months to 1 year of hands-on experience building agentic products or solutions, including tool-using agents, conversational agents, long-running agents, reasoning/planning agents, or similar systems.
• Experience with multiple modern agent frameworks is preferred.
• 1+ year of experience evaluating AI systems for quality, reliability, and safety at scale.
• 5+ years of experience shipping production software in an enterprise or consumer environment, not just prototypes or proofs of concept.
• OpenSearch or Elasticsearch experience is preferred, but comparable experience with other search and retrieval systems is sufficient.
• Expert experience, understanding and knowledge of digital and broadcast production operations and workflows
• Experience working with video, rich visual media, or multimodal AI systems.
• Strong knowledge of industry trends and best practices
• Strong experience with the C4 model and other traditional design artifacts
• Experience working in an Agile environment

Core Competencies

Demonstrates expertise in building and operating production APIs and services, with a strong focus on backend engineering, AI systems, and evaluation techniques. Proficient in architecting scalable search and information retrieval systems while ensuring quality, reliability, and operational safety.

Highest-signal resume keywords

• Backend Engineering Fundamentals
• Production API Design and Operation
• Search and Information Retrieval Systems
• Evaluation of AI Systems
• Experience with Foundation Models

ATS Optimization Keywords

Hard Skills

• Java
• Golang
• Python
• JavaScript
• RESTful APIs
• Asynchronous Workflows
• Statistical Concepts
• Batch Workflows
• Agentic Products
• Digital Production Operations

Soft Skills

• Strong Judgment
• Ownership of Production Systems
• Collaboration Across the Stack

Industry Keywords

• Multimodal AI Systems
• Quality Tradeoff Analysis
• Observability
• Human-in-the-Loop Review
• C4 Model

Tools & Technologies

• OpenSearch
• Elasticsearch
• FFmpeg
• OpenCV
• Agile Methodologies