Forward deployed AI engineer for agentic systems

Proxify; United States; Remoto; USD 150.000 - 230.000; Tempo pieno

Descrizione del lavoro

Proxify ищет опытного инженера по искусственному интеллекту для ведения проектов по созданию агентных систем на базе LLM и RAG. Участник будет работать с архитектурами клиентов и направлять команду инженеров, устанавливая техническую стратегию и сроки, выступая техническим контактным лицом.

Требуется 5+ лет опыта, глубокие знания Python, LangChain, вLLM, PyTorch или TensorFlow, а также опыт контейнеризации и работы в облаках (AWS/GCP/Azure).

Competenze

• 5+ лет в разработке ПО с упором на машинное обучение и генеративный ИИ.
• Опыт вывода LLM, RAG и агентных систем в продакшн и сопровождения их работы.
• Практические навыки с векторными базами данных, несколькими провайдерами LLM и фреймворками (LangChain, vLLM, PyTorch/TF).
• Сильные навыки Python и надёжные инженерные практики (VCS, тестирование, code review) и контейнеризацию в облачных средах (AWS/GCP/Azure).

Mansioni

• Глубокий разбор архитектуры клиента, данных и интеграций.
• Перевод〈scope〉 в агентную систему, работающую в окружении клиента, от начала до продакшна.
• Руководство командой инженеров на проектах и формирование технического направления.
• Держать связь с клиентом как технический контакт, фиксировать изменения в объёме работ.

Conoscenze

5+ years exp

Python

LLM AI

English fluency

Consultative approach

Strumenti

LangChain

vLLM

PyTorch

TensorFlow

Docker

AWS

GCP

Azure

Descrizione del lavoro

Описание:

Founded in 2018 and headquartered in Stockholm, Proxify helps 2,500+ companies worldwide scale their technical teams. The Financial Times ranked us as Sweden's 3rd fastest-growing company in 2025. Our clients increasingly need more than extra engineers. They need someone who can find where AI agents actually pay off and ship them into production.

Задачи:

Get under the hood of each client's architecture, data and integrations. Turn a scoped brief into an agentic system running in the client's own environment, end to end. Lead the engineers on each project and set the technical direction. Be the client's day-to-day technical contact: updates, questions, and the things that were clear on paper but not in practice. Keep several projects moving at once, and surface scope changes instead of agreeing to them on the spot.

Требования:

5+ years in software engineering, with a background in computer science, machine learning and generative AI. A track record of shipping LLM, RAG and agentic systems to production and keeping them running, with the depth to work out why a model behaves the way it does. Hands-on with RAG pipelines (vector databases, streaming, multi-tenancy), multiple LLM providers, and frameworks like LangChain, vLLM and PyTorch or TensorFlow. Strong Python, solid engineering habits (version control, testing, code review) and containerized deployments on AWS, GCP or Azure. Quick to pick up an unfamiliar codebase and build inside someone else's stack. A solution-based, consultative approach. You start from the client's problem, not from the tool or product you'd like to sell them. A strong communicator in professional English. You can lead a client conversation and explain technical decisions to people who'll never read the code. Self-directed. You run with a brief without needing someone to check in on you.

Будет плюсом:

Things you've built on your own time, such as side projects, open source or agent experiments, and the story of why you built them; Real experience with LangGraph, CrewAI, AutoGen or the OpenAI Agents API; Time at a startup or scale-up where priorities shift quickly

Условия:

You'll see a wide range of companies and problems in a short time, so the work never gets repetitive. There's no fixed playbook, so the ownership is real and the systems you build are yours to get right. You'll work directly with clients, with strong backing from leadership to move fast.