Forward-Deployed Ai Engineer

Mission:
As a Forward-Deployed AI Engineer, you will bring the full range of Data & AI expertise - data engineering, data analytics, data science and machine learning - directly into a UAV platform team. You will sit with the engineers and operators who design, test and fly our aircraft in Caldas da Rainha, understand their problems first-hand, and turn them into working data and AI solutions, fast.
You will work with flight logs, telemetry, video and mission data; analyse them to answer engineering questions; build models where they add value; and package the results as internal tools, dashboards and integrations with our mission and ground control software. You will be the bridge between the platform team and Data & AI: bringing in Data & AI's platforms, models and specialists, and feeding the team's needs and domain knowledge back into Data & AI's roadmap. You will work AI-first, using AI-assisted development tools such as Claude to prototype quickly, validate with users, and harden what proves useful.
We are looking for a deeply technical generalist - a data scientist, ML engineer or data engineer with strong software skills - who enjoys working close to the product and the people using it, and who would rather ship a useful solution this week than a perfect one next quarter.
What will be your responsibilities:
Data Analytics & Data Science:
Analyse flight logs, telemetry and mission data to answer engineering questions - e.g. flight performance, anomaly detection, post-flight review, test and validation analysis;
Machine Learning:
Identify where ML adds value for the team, then build, evaluate and iterate on models - from quick baselines to production candidates - together with Data & AI's data science and ML engineering teams;
Data Engineering:
Help make the team's data easy to collect, find and trust - ingestion of logs and video, consistent mission identifiers, documented and queryable datasets;
Internal Tooling:
Design, build and maintain internal tools - scripts, CLIs, small web apps, dashboards and automations that remove manual work from engineering, testing and flight operations;
Rapid Prototyping:
Use AI-assisted development workflows (e.g. Claude, Claude Code or similar) to go from a problem to a working prototype in days, test it with users, then iterate or harden it;
Systems Understanding & Integration:
Build a working knowledge of how our software fits together - mission and ground control software, onboard and ground data flows - so you can integrate with it, debug across it and explain it to others;
Bridge to Data & AI
: Be the platform team's day-to-day point of contact for Data & AI. Translate needs into clear, scoped requirements, bring in the right Data & AI teams, and help the platform team adopt their products;
Field & Test Support:
Support ground and flight tests when needed, making sure tools, models and data pipelines work in real-world conditions;
Documentation & Knowledge Sharing
: Document analyses, tools and data flows, and share AI-assisted ways of working with the team;
Agile Delivery:
Work within the team's agile rituals, keep work visible in Jira and Confluence, and prioritise with the platform team's Product Owner.
Profile and requirements:
Education:
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Aerospace or Electrical Engineering, or a related field.
Experience
: 3+ years of hands-on experience delivering data, analytics or ML solutions end to end, in a data science, ML engineering, data engineering or similar role - ideally including time spent working directly with end users or customers.
Strong skills in exploratory data analysis, statistics and visualisation, especially on time-series, logs or sensor data.
Strong SQL and Python data stack (pandas/Polars, NumPy, Jupyter).
Hands-on experience training, evaluating and iterating on ML models (e.g. scikit-learn, PyTorch), including choosing the right metrics and validation approach.
Good judgement on when a model is the right answer and when a simpler analysis or rule is enough.
Strong Python; experience with at least one of C#, C++, TypeScript/JavaScript is a plus.
Experience building internal tools end to end:
scripts and CLIs, dashboards or simple web apps (e.g. Streamlit, Dash, React), REST APIs.
Ability to read, understand and integrate with existing systems you did not write - APIs, file formats, message buses, databases.
Comfortable with Git, Linux, Docker and basic CI/CD.
AI-Assisted Development (essential):
Hands-on experience using AI coding assistants and agents (e.g. Claude, Claude Code, Cursor, Copilot) to prototype and ship quickly, with the judgement to review, test and verify what they produce. Additional training can be provided in-house, but affinity, some form of experience and strong openness to these new way