Senior AI Engineer - LLM & Production Systems

Jobgether • Switzerland

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AI Summary

Build and deploy production-grade AI-powered features using LLMs, RAG, and agents. Lead end-to-end AI integration from prototype to scalable systems. Collaborate with cross-functional teams to solve complex business challenges with pragmatic AI solutions.

Key Highlights

Hands-on role focused on bringing AI-powered capabilities into real-world products and production workflows

Design, build, deploy, and continuously improve LLM-powered features in a large-scale environment

Strong emphasis on production-grade AI systems, evaluation, observability, and cost optimization

Key Responsibilities

Architect, develop, deploy, and maintain production-grade LLM capabilities integrated into customer-facing products and internal workflows

Build backend services, APIs, integrations, and supporting infrastructure that connect AI capabilities with product functionality

Implement production-ready patterns involving LLMs, RAG, embeddings, vector search, agents, and tool calling

Design reusable components, abstractions, and engineering patterns that improve development velocity, consistency, and maintainability

Establish and improve evaluation frameworks, observability, monitoring, and feedback loops for AI-powered features

Monitor and optimize AI systems for quality, latency, reliability, scalability, and inference cost

Investigate production issues, analyze telemetry, and continuously improve AI functionality based on system performance and user feedback

Collaborate closely with Product, ML, and Engineering stakeholders to translate product challenges into practical AI solutions

Rapidly prototype and validate new ideas, then transform successful experiments into robust and maintainable production systems

Contribute to engineering decisions around architecture, trade-offs, scalability, and long-term technical sustainability

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Technical Skills Required

Python Large Language Models (LLMs) AI Production Systems

Benefits & Perks

$500 home-office setup budget

$1,000 annual learning and development budget

Flexible work-from-home arrangement

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Nice to Have

Experience with multi-agent systems, MCP, guardrails, moderation, safety checks, prompt and context management, routing, caching, or fallback strategies

Experience with Docker and cloud platforms such as AWS, GCP, or Azure

Experience with modern frontend development and customer-facing web applications using Angular, JavaScript/TypeScript, Node.js

Job Description

This is a hands-on engineering opportunity focused on bringing AI-powered capabilities into real-world products and production workflows. You will design, build, deploy, and continuously improve LLM-powered features within a large-scale technology environment. The role combines strong software engineering with practical expertise in RAG, embeddings, agents, tool calling, and AI orchestration. You will work closely with Product, ML, and Engineering teams to turn complex business challenges into pragmatic and scalable AI solutions. Beyond implementation, you will help establish robust evaluation, observability, monitoring, and feedback practices for production AI systems. The environment is fast-moving and product-focused, offering significant ownership and opportunities to experiment, iterate, and ship. This role is particularly suited to an engineer who enjoys taking AI capabilities from prototype through reliable, maintainable production systems.

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