AI Engineer Viana do Castelo

AI Engineer
Viana do Castelo
Viana do Castelo, Viana do Castelo District, Portugal

Job Title: AI Engineer

Location: Remote (Portugal, Spain, Bulgaria, Romania)

Type: Full-time

About Us

Oraion is your single source of truth for enterprise data. Oraion uses agentic AI to turn structured and unstructured enterprise data into
- obvious insights, instantly.

Oraion helps you make faster, more informed decisions and even automate complex tasks, all through a
- serve,
- based AI agent embedded in your existing workflow such as Slack, Teams or via our Enterprise Intelligence Platform.

We’re looking for an AI Engineer to help us push the boundaries of intelligent agents in
- world enterprise environments. You’ll build robust,
- grade agentic and machine learning systems that connect insights to action.

About the Role

As an AI Engineer at Oraion, you’ll work across the full lifecycle of AI systems: from
- tuning open source models and prompt engineering to agent orchestration and performance monitoring. You’ll be instrumental in shaping how our agents interact with enterprise data, uncover insights, and automate analysis within a secure and scalable infrastructure.

This is a
- on role with a strong engineering core. You’ll partner closely with data engineers, product managers, and UX designers to bring agent capabilities into our
- tenant Saa
S application, focusing on performance, reliability, and measurable value to the end user.

Responsibilities

Design, build, and deploy
- grade agentic AI systems using frameworks like Lang
Chain, Lang
Graph, and Lang
Smith

Implement scalable Retrieval-Augmented Generation (RAG) pipelines, including embedding strategies, vector DB integration, and query optimisation

Fine-tune and evaluate LLMs for
- specific tasks including summarisation, classification, clustering, and conversational reasoning

Develop and maintain ML pipelines for NLP tasks such as sentiment analysis, topic modeling, and document clustering

Continuously monitor and evaluate agent behaviour in production, using agent evaluation frameworks and performance metrics

Integrate agents with internal systems via Model Context Protocol (MCP) or similar communication standards

Collaborate with backend and data engineering teams to ensure seamless integration of AI components into our data platform

Optimise AI workflows for latency, accuracy, and cost in a
- tenant,
- scale environment

Participate in the research and adoption of emerging tools, models, and frameworks to maintain a
- edge stack

Requirements

1. 5+ years experience with LLM’s and Agentic systems and 3+ years  experience in AI/ML engineering or backend engineering roles.

Deep understanding of agentic architectures and experience deploying AI agents to production

Expertise with Lang
Chain, Lang
Graph, Lang
Smith or similar tools for orchestrating agents

Strong practical experience with RAG systems and vector databases.

Experience building and monitoring ML models in production environments (ML Ops experience)

Skilled in LLM
- tuning and prompt engineering for
- specific tasks

Proficient in unsupervised learning techniques for clustering, categorisation, and discovery

Familiarity with Model Context Protocol (MCP) or similar standards for
- system integration

Strong coding skills in Python (and optionally Rust), with API development experience

Experience working with
- tenant Saa
S applications and secure enterprise data environments

Startup experience or a bias for fast, iterative delivery is a plus

Bonus Points

Experience integrating agents into messaging platforms (Slack, Teams, etc. )

Knowledge of
- grade data governance and access controls (e. g. ABAC)

Previous work with
- time data workflows and streaming architectures

Exposure to knowledge graphs or
- driven reasoning systems

Familiarity with tools like Dagster, dbt, and Apache Iceberg in the broader data stack

What We Offer

Ground-floor opportunity to shape agentic AI at a
- growing startup

Collaborative team with deep experience across data, product, and AI

Competitive compensation

Remote-friendly, flexible working culture

Access to
- edge LLMs, tools, and a
- thinking product vision