Lead AI Engineer – Production LLMs & Agent Systems

Proxify; Stockholms kommun; On-site; SEK 900,000 - 1,300,000; Full time

Benefits offered by this job

Stockholm-based role

Occasional client visits

Job summary

Proxify, founded in 2018 and headquartered in Stockholm, is seeking an AI engineer to work closely with clients. You will dive into client architectures, data, and integrations to shape what to automate and drive production-ready solutions.

You will lead Proxify engineers on projects, collaborating with the AI Product Manager and shipping agentic systems using LangChain, LLMs, and RAG pipelines in client environments from discovery to production. Stockholm-based with some travel.

Qualifications

• 5+ years in software engineering with a CS and ML background.
• Proven track record shipping LLM, RAG and agentic systems to production.
• Experience with LangChain, vLLM, PyTorch or TensorFlow and multiple LLM providers.
• Strong Python and containerized deployments on AWS, GCP or Azure.
• Excellent professional English communication and client-facing skills.

Responsibilities

• Get under the hood of each client's architecture, data and integrations.
• Turn a scoped brief into an end-to-end agentic system in the client's environment.
• Lead the engineers on each project and set the technical direction.
• Be the client’s day-to-day technical contact and manage updates.
• Keep several projects moving and surface scope changes promptly.

Skills

LLM deployment

RAG pipelines

Python

Cloud deployments

Client communication

Team leadership

Education

CS background

Tools

LangChain

vLLM

PyTorch

TensorFlow

OpenAI API

Vector databases

Job description

Proxify, founded in 2018 and headquartered in Stockholm, is seeking an AI engineer to work closely with clients. You will dive into client architectures, data, and integrations to shape what to automate and drive production-ready solutions.

You will lead Proxify engineers on projects, collaborating with the AI Product Manager and shipping agentic systems using LangChain, LLMs, and RAG pipelines in client environments from discovery to production. Stockholm-based with some travel.