What is DareData?
DareData is a network of professionals that perform services and build products, creating value from data. We are a community of freelancers that work under a common brand because it furthers our professional interests. By applying to this position you are declaring your intention to enter our network.
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What Does DareData Do?
DareData has two main lines of business: Consulting and our own AI product suite, Gen-OS.
Gen-OS, Our AI Product Suite
Gen-OS is DareData's proprietary enterprise AI platform, built and maintained by our own network of engineers. It is deployable infrastructure that gives organisations the foundation to build, govern, and scale their own AI agents, with security, observability, and model management baked in from day one. Gen-OS is our answer to the growing demand for reliable, governed, and customisable AI inside enterprise environments. On top of the Gen-OS Platform, we have developed two flagship products:
GenAssistant: An enterprise-grade AI assistant that brings governed, context-aware AI to knowledge workers across the organisation. GenAssistant is currently deployed at leading retail and real estate groups, including Sonae Sierra, where it supports thousands of employees with search, summarisation, and task automation across internal knowledge bases.
Gen-Service: An AI-powered internal helpdesk and employee support automation product. Gen-Service handles repetitive IT, HR, and operations queries at scale, routing and resolving requests intelligently so that support teams can focus on higher-value work. It integrates natively with existing enterprise systems and ticketing platforms.
Working on Gen-OS means you will be involved in cutting-edge agentic AI development, model governance, custom agent design, and the full lifecycle of an AI product, from architecture to production. As an AI Engineer at DareData, you may be asked to contribute to Gen-OS projects alongside client-facing consulting and outsourcing work.
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Consulting
Consulting is about doing projects that have a beginning, middle, and an end. In these projects we help a client solve a problem that they don't have the knowledge to solve themselves. Although there are exceptions, consulting projects are typically shorter or have less hourly work associated with them. Each engagement must be scoped, sold, won, budgeted, staffed, and executed in order to achieve some desired business outcome. In consulting engagements we are largely autonomous and manage ourselves. Consulting is inherently unpredictable but many people consider it very stimulating.
What Happens When I Join?
When you join DareData, you will gain access to job openings across several industries and problem domains. Our job is to match you with the right opportunities based on your profile and expectations, and ensure the projects are completed successfully. You can also declare your interest in particular positions by applying through our internal system.
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Job Description - AI Engineer
We are looking for AI Engineers who are passionate about building real AI products that work in production. Since we run into quite a variety of tech stacks, the most important thing is to have strong fundamentals in software and AI engineering, solid hands-on experience with the modern AI development toolchain, and the ability to learn quickly.
Requirements
* Full working Python proficiency (2+ years of professional experience).
* Hands-on experience building and deploying LLM-powered applications in production.
* Experience designing and implementing agentic AI systems — autonomous agents, multi-agent pipelines, tool-use, and orchestration frameworks (e.g. LangChain, LangGraph, or similar).
* Solid understanding of prompt engineering, RAG (Retrieval-Augmented Generation), and vector databases (e.g. Chroma, Weaviate, Pinecone, pgvector).
* Familiarity with LLM APIs and SDKs — OpenAI, Anthropic, Azure OpenAI, or open-source models via HuggingFace or Ollama.
* Experience with common software engineering tools and processes: Docker, Git, CI/CD, unit and integration testing.
* Ability to turn business requirements into AI architectures and communicate technical trade-offs to non-technical stakeholders.
* Knowledge of modern MLOps and AI Ops practices: model evaluation, observability, guardrails, and keeping models healthy in production.
* Based in Portugal
By submitting your application, you confirm that you consent to your data being stored with the sole purpose of contacting you regarding this application.
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You also confirm you agree with DareData's Vision, Mission, Values and policy of inclusivity. You can read more about working with /working-at-daredata. Check our culture document before applying: