AI Engineer

Inetum; Lisboa; Híbrido; EUR 55 000 - 85 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Hybrid work regime

Office in Lisbon or Porto

Professional growth opportunities

Resumo da oferta

Inetum is seeking an AI Engineer to join its team, contributing to a culture of innovation. The role focuses on building production-ready AI agents for back-office use cases in a regulated financial environment.

You will work with Python, LangGraph, LangChain, Docker and Kubernetes, design prompts, test agents, and collaborate with business analysts to translate operations like settlements and reconciliations into agent behavior, with hybrid work in Lisbon or Porto.

Qualificações

• 3–6 years of Python engineering experience.
• Experience with at least one agent framework (CrewAI, LangGraph, LangChain or AutoGen).
• Solid grasp of prompt engineering, RAG patterns and LLM evaluation techniques.
• Comfortable consuming REST/gRPC APIs and async Python.

Responsabilidades

• Design, build, and improve AI agents, including reasoning flows and tool use.
• Develop agents in Python using LangGraph, LangChain, and internal SDK.
• Design agent workflows with task decomposition, API tool calls, memory/state handling and guardrails.
• Manage prompts and configurations via Kubernetes ConfigMaps with release discipline.
• Run agent evaluation using datasets, regression suites, and quality metrics.
• Instrument agents with observability: logging, token usage, latency, and failure modes.

Conhecimentos

Python

LLM / GenAI

Agent framework knowledge

Prompt engineering

Testing culture

Ferramentas

LangGraph

LangChain

CrewAI

AutoGen

Docker

Kubernetes

pytest

Descrição da oferta de emprego

We are looking for an AI Engineer to join our Inetum Team and be part of a work culture focused on innovation!

Location: Lisbon or Porto

Main Tasks

• Design, build, and continuously improve AI agents, including their reasoning flows, tool use, prompts, and evaluation frameworks.
• Develop and maintain agents in Python using LangGraph, LangChain, and an internal SDK, and adapt central general-purpose agents (drafting, summarisation, process orchestration) to custody back-office use cases.
• Design agent workflows covering task decomposition, tool and function calling against APIs, memory and state handling, guardrails, and human-in-the-loop checkpoints appropriate to back-office controls.
• Engineer, test, and version prompts, and manage prompt and configuration changes through Kubernetes ConfigMaps with proper release discipline.
• Build and run agent evaluation using golden datasets from real back-office cases, regression suites, quality metrics (accuracy, groundedness, escalation rate), and shadow testing before rollout.
• Instrument agents for observability through structured logging of reasoning traces, token usage, latency, and failure modes, and handle model lifecycle concerns including provider changes, context window constraints, and cost/latency trade-offs.
• Work daily with the Business Analyst to translate operational knowledge (settlements, corporate actions, client queries, reconciliations) into agent behaviour.

Profile

• 3 to 6 years of Python engineering experience, with at least 1 to 2 years on LLM/GenAI applications.
• Practical experience with at least one agent framework such as CrewAI, LangGraph, LangChain, or AutoGen, with understanding of ReAct-style loops, tool calling, and structured outputs.
• Solid grasp of prompt engineering, RAG patterns, and LLM evaluation techniques.
• Comfortable consuming REST/gRPC APIs (Go backend), JSON schema design, and async Python.
• Working knowledge of Docker and Kubernetes, including deployment, log reading, and ConfigMap editing.
• Strong testing culture with experience in pytest, mocking LLM calls, and deterministic test design for non-deterministic systems.

Additional Information

• Hybrid work regime – office in Lisbon or Porto.
• Integration into a newly created 5-person squad maintaining and evolving a portfolio of production AI agents for the securities services (custody) division of a major European bank.
• Exposure to cutting-edge AI agent technologies in a complex and regulated financial environment.
• Opportunities for professional growth and development.
• Collaborative and innovative work environment.