Artificial Intelligence Engineer

Point-out; Italia; Remote; EUR 30,000 - 40,000; Full time

Benefits offered by this job

€30-40k gross per year

10% annual bonus

Fully remote, permanent

Job summary

Point-out is hiring an AI Engineer to design, build, and operate agentic workflows at the core of our platform. You will turn prototypes into production-grade services, with the CTO pairing on tough problems to deliver observable,-monitored agents.

The role is junior to mid-level, remote, and involves hands-on work across LLM reasoning, tool use, retrieval, and classifier training to improve speed, cost and reliability.

Qualifications

• Solid Python engineering with clean, tested code and API design.
• Experience modeling and querying data; verify data quality before modeling.
• Familiar with agent workflows, prompting, tool use, memory, guardrails and LLM failure modes.
• Ability to design evals and metrics; use tracing tools to understand agent behavior.
• Experience deploying services on AWS or other cloud platforms; Docker-based deployment.

Responsibilities

• Turn platform use cases into precise requirements (inputs, outputs, latency, cost).
• Scout and test models/frameworks on real tasks; advise on adoption.
• Prototype multi-step agents with LLM reasoning, tools, retrieval and structured outputs.
• Build eval sets and metrics; measure quality, latency, costs, failures.
• Deploy agents as services on AWS; integrate via clean APIs.
• Instrument agents with tracing/evaluation; monitor data drift before customers.
• Document architecture decisions, prompts, evaluation results and runbooks.
• Train supervised classifiers to replace generators when faster or cheaper.

Skills

Python engineering

Data modeling & SQL

Agent frameworks

Observability & eval

Cloud & deployment

AI-native working

Bilingual communication (Italian & EN)

Tools

LangChain/LangGraph

LlamaIndex

Strands Agents

Docker

AWS

Job description

Point-out is hiring an AI Engineer to build the agentic AI workflows at the heart of our platform. You'll take agents from prototype to production and keep them measurably good, working side by side with our founder CTO.

About Point-out

Every day, millions of people ask AI what to buy, whom to believe and how to stay informed. AI assistants' answers have become a new medium where knowledge takes shape and choices are guided. We want to understand how that happens.

We're a team born of the friction between physics, economics and communication. We build intelligence products that measure, and make legible, how the media, AI models and AI agents select their sources and portray companies and people.

Our platform for GEO (generative engine optimization) and GEA (generative engine advertising) measures how a brand and its competitors appear in AI searches on ChatGPT, Gemini, Perplexity and Claude. It identifies what to do about it across owned channels, earned media and paid investments, and helps marketing and communication teams act within the tools they already use. We're building from Italy with expansion to other European markets planned. We recently closed our first funding round and are preparing the next.

The role

You'll design, build and operate the agentic workflows behind our most advanced use cases:

• digital twin simulation of AI searches;
• complex classification;
• crawlability audits;
• editorial recommendations;
• MCP integrations with general-purpose AI assistants.

This is a hands-on, junior to mid-level role. The CTO will pair with you on the hardest problems, and you'll take ideas from prototype to a running, monitored service with growing autonomy.

What you'll do

• Turn platform use cases into precise requirements: inputs, outputs, quality criteria, cost and latency constraints.
• Scout and test models, frameworks and managed services on our real tasks and data, and recommend what to adopt, watch or ignore.
• Design and prototype multi-step agents that combine LLM reasoning, tool use, retrieval and structured outputs.
• Build evaluation sets and metrics; measure output quality, token cost, latency and failure modes; decide with the CTO when a solution is ready to ship.
• Deploy agents as services on AWS (Amazon Bedrock AgentCore and containers) and integrate them through clean, documented APIs.
• Instrument every agent with tracing and evaluation (Langfuse) and catch data and quality drift before it reaches customers.
• Document architecture decisions, prompts, evaluation results and runbooks so the next engineer can pick up where you left off.
• As labelled data grows, train supervised classifiers (scikit-learn, PyTorch) to replace generative models where they're faster, cheaper and more predictable.

What we're looking for

• Solid Python engineering: clean, tested, version-controlled code (Git/GitHub), sound architecture and API design. You're confident with pandas and familiar with scikit-learn and PyTorch.
• Data and SQL: you can model, query, join and shape data, and you check data quality before model quality
• Agent frameworks: you've built agentic or RAG workflows with LangChain/LangGraph, LlamaIndex, Strands Agents or similar, and you understand prompting, tool use, memory, guardrails, structured outputs and typical LLM failure modes
• Observability and evaluation: you can design evals, define metrics and use tracing tools like Langfuse to understand what an agent actually did and why
• Cloud and deployment: you know Docker and have deployed services on AWS or another cloud, getting from your laptop to a running, monitored service
• AI-native way of working: you build with tools like Claude Code and judge their output critically
• Clear communication in Italian and English, with technical and non-technical colleagues alike

Nice to have

• Amazon Bedrock AgentCore, Bedrock model APIs or other managed agent runtimes; AWS certifications.
• Infrastructure as Code (Terraform, AWS CDK, CloudFormation), CI/CD pipelines, Kubernetes.
• Building or integrating MCP servers with Claude, ChatGPT or Gemini.
• Supervised text classifiers shipped to production.
• Web crawling, technical SEO or GEO.
• Experience in an early-stage startup or small product team.

What we offer

• €30 - 40k gross per year, depending on experience.
• 10% annual bonus (50% on personal performance, 50% on company performance).
• Permanent, full-time contract, fully remote.