Top Artificial Intelligence Jobs in Lisbon

Architect and build production AI-powered HR systems using agentic workflows, multi-agent systems, APIs, and workflow automation. Integrate Workday and other HR tools, implement governance, audit logging, privacy controls, and human approval gates, and ensure reliable payroll-adjacent workflows. Document solutions, train People team users, drive adoption, and measure automation impact. The role requires strong software engineering, AI application development, HR technology, Workday, data privacy, and workflow automation experience.

Build and operate shared AI platform infrastructure for LLM applications, agents, RAG, tool calling, and AI workflows. Develop data and knowledge pipelines, secure enterprise integrations, reusable frameworks, deployment and observability standards, and developer tooling. Take AI systems from experimentation to reliable production while ensuring security, privacy, governance, scalability, quality, and cost efficiency. Collaborate across Engineering, Product, and IT to establish practical AI platform patterns and guardrails.

Design, build, and maintain automated test suites, evaluation scenarios, metrics, and datasets for AI-powered features. Automate QA workflows with Python and CI/CD, test APIs and ML model outputs, define quality strategy and acceptance criteria, create CI/CD quality gates, mentor teams, participate in code reviews, and document findings.

Design, build, and maintain scalable backend systems and APIs for specialized AI assistants (helpdesk, HR, back office). Ensure secure data handling, integrate LLM-driven features, collaborate with front-end teams, and participate in agile processes, code reviews, and continuous architecture improvements.

Define and lead implementation of scalable, secure AI/GenAI architectures (LLMs, RAG, vector DBs, agents). Set technical standards, build PoCs, integrate models with enterprise systems, ensure governance, and mentor engineering teams while supporting presales and client engagements.

Develop and maintain a multi-cloud GenAI platform: design, implement, test, deploy scalable APIs and backend services, build monitoring and KPIs, automate workflows, ensure security/compliance, and collaborate with international teams to continuously improve platform capabilities.

Design and build AI-driven conversational flows and integrations using LLMs, prompt engineering, REST APIs, and modern backend practices. Collaborate with multidisciplinary teams to influence product direction, write and refactor scalable code, and implement solutions in cloud environments (Azure/AWS).

Lead design and build Generative AI applications using LLMs and Azure AI services. Implement, deploy (Azure ML, CI/CD), integrate semantic search and embeddings, handle data engineering, and present solutions to stakeholders.

Lead design and build of an end-to-end AI contract-review agent: prompt orchestration, RAG pipelines, fine-tuning, web UI and tooling, data/model infra, deployment (CI/CD/cloud), and product-driven features like assumption mapping and contract diagnostics.

The AI Creative Executor will lead AI-enabled marketing campaigns, blending storytelling with technology, managing end-to-end production and collaborating with the marketing team to ensure alignment with brand standards.

The Senior AI Compute Infrastructure Engineer will manage and optimize GPU and accelerator clusters for AI workloads, collaborate with teams, and ensure reliable performance and cost efficiency.

Provide research and advisory to global CFOs and Controllers on transforming controllership processes (AP, AR, financial close) using AI, automation and finance technologies; produce published research, vendor evaluations, and client-facing presentations; collaborate with analysts and deliver strategic, actionable recommendations to improve financial reporting and automation outcomes.

Lead product development in the industrial sector focusing on IoT, edge computing, and AI applications. Oversee product lifecycle, conduct market research, and collaborate with cross-functional teams.

Lead engineering enablement across eight companies to cascade CTO AI vision into team discipline. Detect and package successful practices, run cross-company diffusion, operate cadence of validation and demos, measure adoption and outcomes, triage deeper needs to PoCs/workshops, and capture reusable artifacts and metrics.

As a Staff/Senior AI Product Engineer, you will build AI-powered product features, enhance the tech stack, and design AI workflows while collaborating with product teams. Your focus will be on agent-native architecture and improving the codebase for AI agents.

Define and execute the product roadmap for AI-driven blockchain security monitoring tools. Collaborate with cross-functional teams, analyze market and customer feedback, deliver features on time, and communicate with stakeholders to align expectations and improve product offerings.

Design and build production-grade multi-agent AI systems: orchestration, routing, memory, tool execution, multimodal workflows, and integrations with model providers and platform APIs. Implement testing, observability, and reliability practices; analyze and extend APIs and codebases to improve agent behavior, performance, and robustness in gaming and transaction-heavy domains.

Manage curriculum development for data science and engineering, collaborate with instructors, create content, and drive improvements based on learner feedback.

As a Curriculum Manager, you will manage content development for the data science and engineering curriculum, collaborating with instructors and teams to enhance learning experiences.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

Own and improve Primer's GTM intelligence: maintain dashboards and semantic models, train BI/LLM models (Omni/Claude), surface pipeline/account signals, ensure correct Salesforce modeling, build revenue-driving models and GTM AI workflows, partner with data engineering and RevOps, drive adoption, and promote self-serve data literacy.

Design polished, user-centric mobile and web interfaces for BJAK's AI and financial products. Create wireframes, flows, prototypes and high-fidelity UI, maintain the design system, collaborate with PMs and engineers, iterate using feedback and analytics, and ensure accessibility and responsiveness across devices.

Design and implement execution primitives for AI/agent workflows in Kestra's Java core, build and maintain plugins to connect LLM providers and agent frameworks, convert agent use cases into reusable blueprints with product, and ensure AI executions are observable, debuggable, correct, and reliable.

Own AI workflows product: discover and validate AI use cases with customers, define roadmap and specs, create reusable blueprints with engineering, and prioritize what not to build.

Design and build scalable, accessible frontend applications for AI-driven Contact Center and UC products. Implement responsive interfaces with Angular/React, integrate with backend AI services (REST/GraphQL), optimize performance, participate in architecture and code reviews, and collaborate with cross-functional teams in an Agile environment.