Top Artificial Intelligence Jobs in Lisbon

Lead development and adoption of Medical Insights capabilities across Medical Affairs, applying advanced analytics and AI to translate medical data into actionable insights. Drive strategy, governance, use-case prioritization, tool requirements, stakeholder alignment, value measurement, and adoption to inform evidence generation, medical strategy, and decision-making across cross‑functional and global teams.

Own and operate the International Commercial build engine from data foundation to production AI. Deliver governed data platforms, reusable agentic AI and production-grade engineering via a shared deployable pool, vendor/SI management, platform integration with CIO, AI evaluation/red-teaming, AgentOps, run/BAU, observability, cost control and cross-functional stakeholder alignment to ensure reliable, compliant, and reusable solutions in production.

Lead global marketing and corporate communications to define Multiverse's narrative, positioning, and GTM for AI/quantum products. Partner with the CEO, build and scale the marketing & communications team, own product messaging, PR, executive positioning, agency relationships, and measure impact on awareness and enterprise pipeline.

Own partnership sourcing, negotiation, and deal execution to drive adoption of Walrus across AI and Web3 ecosystems. Build relationships with AI builders, data vendors, compute networks, and web3 partners; lead contract negotiations; and manage cross-functional integration from signing through execution.

The Principal Engineer will lead the design and delivery of core platform capabilities, focusing on scalable systems, AI application, and mentoring engineers while driving architectural decisions and improving operational systems.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

Lead AI-driven IT projects from concept to delivery: plan and govern project execution, manage risks and progress, coordinate cross-functional teams and external vendors, implement automation and intelligent agents, and report to executives while ensuring alignment with business objectives.

Develop and maintain scalable full-stack applications using .NET and React. Integrate cloud architectures, APIs, and generative AI/LLM capabilities. Build AI agents, intelligent automation, and workflow orchestration. Apply DevOps/CI-CD practices, ensure secure high-performance solutions, and work in an agile hybrid environment (3 days onsite). Portuguese fluency required.

Administer and maintain Windows and Linux servers, cloud infrastructure (Azure/AWS), and Microsoft 365. Implement monitoring, automation, performance optimization, AI platforms, and intelligent services. Ensure secure, scalable, highly available systems with strong scripting (PowerShell/Bash), IAM, observability, and cybersecurity best practices. Provide hybrid on-site support in Lisbon.

Build full-stack software that turns satellite intelligence into mission-critical decisions. Architect and implement deterministic multi-agent orchestration, geospatial RAG with distributed vector consistency for DDIL environments, optimize high-concurrency spatial indexing and queries, and integrate AI/LLM workflows across cloud and edge. Collaborate cross-functionally, ship production systems, and prepare for forward-deployed, customer-facing engineering roles.

Architect and build an AI-native automation and orchestration toolchain (fusing traditional tools with foundation models), enable and mentor early adopter teams, standardize practices across departments, drive infrastructure-as-code and CI/CD adoption, contribute to the IT/Sec operating system, and champion cross-departmental adoption of automation and AI platforms.

Evaluate AI-generated coding interactions end-to-end, judging usefulness, high-level correctness, engineering judgment, and quality of explanations. Provide clear, opinionated feedback, distinguish response quality levels, and help define best practices for AI-assisted developer workflows.

Build and maintain evaluation, synthetic testing, and validation tooling for AI agents. Design backend services, APIs, and event-driven test infrastructure, deliver polished front-end features, collaborate with cross-functional teams, and raise engineering quality while mentoring others.

Lead deployment and integration of AI solutions, bridge research and engineering, design scalable AI workflows, integrate and validate model performance and reliability, and collaborate across teams while travelling to support implementation across markets.

As an AI/ML Engineer, you will develop and optimize machine learning models for mobile applications, collaborate with teams, and analyze data to enhance user experience.

As an AI Product Manager, you will lead the development of AI-powered features, collaborating with cross-functional teams to align products with user needs and business goals, while overseeing the product lifecycle.

The Principal AI/ML Scientist & Engineer will lead a team, focusing on AI/ML strategy and developing data products for business outcomes.

Build, deploy, monitor, and optimise production-grade agentic and LLM systems to detect and prevent risk and fraud. Design agent orchestration, RAG pipelines, and LLM serving while writing production-quality Python, querying large structured datasets with SQL, and implementing ML evaluation, observability, and graceful degradation.

Build end-to-end full-stack AI features on a Ruby on Rails backend and React frontend, design and run experiments (A/B tests and AI evaluations), implement AI infrastructure for reliable LLM inference, and iterate quickly to scale production-ready LLM-powered products.

Work with traders, asset operators, and developers to analyze electricity market outcomes, improve trading and operational strategies, and drive customer success. Translate market workflows into product requirements, collaborate with engineering to enhance analytics, dashboards, and optimization models, and lead customer onboarding, implementation, and ongoing technical account management.

The Senior AI Engineer develops and maintains machine learning applications, focusing on NLP and statistical methods to enhance customer experience and innovate product offerings.

The Product Owner for Payments & Finance will manage product initiatives, enhance financial workflows, and leverage AI for operational efficiency.

Evaluate AI-generated coding interactions, assess quality of engineering judgments, provide feedback, and define standards for AI coding agents. Comfortable making subjective judgments about engineering quality.

The role involves designing and operating AI solutions, such as LLM-enabled workflows and integrated systems, ensuring production standards.