Top Artificial Intelligence Jobs in Lisbon

Build and operate production AI agents for fund-operations workflows, including architecture, orchestration, evaluation, observability, deployment, authorization, and human-in-the-loop controls. Develop shared AI platform capabilities, regression testing, provider fallback, regional failover, and document extraction. Improve agent accuracy, latency, and cost while establishing reusable engineering patterns and mentoring other teams.

Join Welo Data’s global contributor network for flexible, remote AI projects. Depending on skills, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with compensation and requirements provided before each assignment.

Analyze production Voice AI agent behavior using transcripts, logs, outputs, and operational data. Investigate hallucinations, failures, anomalies, and quality degradation; develop AI evaluation frameworks, monitoring systems, and dashboards; measure business and patient experience impact; and translate findings into product improvements with Product, Engineering, QA, and Operations teams.

Owns commercial success, revenue, and strategic relationships for embedded HR technology partners. Responsibilities include managing a $10M+ annual bookings target, developing partner sales motions, enabling partner sellers, driving pipeline and ARR growth, resolving commercial issues, leading executive business reviews, expanding partnerships, coordinating cross-functional teams, and managing partner account managers and embedded sales leads.

Lead the company’s Physical AI research and engineering function as a hands-on technical leader. Define research priorities, design and train Transformer-based models, establish rigorous offline and real-world evaluations, integrate systems with physical robots, and analyze failures across data, models, hardware, and environments. Build a focused team, guide technical architecture and experiments, translate customer needs into requirements, and deliver measurable improvements through deployed models, benchmarks, evaluation systems, or data products.

Develop and implement artificial intelligence solutions using machine learning, generative AI, and large language models. Translate business needs into scalable AI applications, work with data processing and APIs, evaluate and improve models, and operate within modern cloud environments and Agile teams. Strong English communication and continuous learning are expected.

Develop and deploy production LLM-driven systems for requirements management and hardware engineering. Build agentic workflows using tool-calling, planning, sub-agents, MCP servers, and orchestration frameworks. Create evaluation pipelines, metrics, benchmarks, and test suites to improve AI accuracy, speed, and cost. Collaborate with software engineers, product managers, and designers in an agile environment throughout the AI product lifecycle, from experimentation through deployment and continuous improvement.

Own the AI cost visibility product end-to-end, building Go backend services, APIs, and TypeScript/React interfaces. Translate cloud AI spend and usage data into clear FinOps experiences, while driving architecture, reliability, monitoring, and iteration. Collaborate closely with customers and product stakeholders, use AI throughout the engineering workflow, mentor peers, and shape product direction in an ambiguous market.

Own the AI cost visibility product end to end, developing Go backend services, APIs, data processing, and TypeScript/React interfaces. Translate AI spending data into clear FinOps experiences, work closely with customers and product needs, and use AI throughout the engineering workflow. Lead feature design, implementation, release, monitoring, and iteration while setting engineering standards, mentoring peers, and building scalable cloud-based SaaS capabilities.

Own AI cost visibility features end-to-end, from customer problem discovery and system design through implementation, release, monitoring, and iteration. Build scalable Go backend services, APIs, and TypeScript/React interfaces that process and present cloud AI spend data. Apply AI throughout the engineering workflow, contribute to product direction, understand FinOps and AI economics, mentor peers, and uphold reliable engineering practices.

Design and lead trusted AI experiences across Intermedia products, including copilots, conversational interfaces, recommendations, automation, and agentic workflows. Own initiatives from research through launch, creating journeys, prototypes, high-fidelity designs, and design-system patterns. Collaborate with Product, Engineering, AI/ML, Research, Security, Privacy, and Legal teams while establishing transparency, user control, accessibility, and responsible AI practices. Mentor designers and help shape the organization’s overall AI interaction language.

Build and operate production LLM-powered internal tools, automations, and customer-facing AI features. Own technical decisions, backend services, multi-service architectures, databases, containerized workloads, monitoring, reliability, incident response, and LLM evaluation workflows. Partner with product, security, and R&D teams while balancing AI quality, latency, and cost. Evaluate emerging AI technologies and contribute to reliable, secure production systems.

Build and operate Typeform’s internal AI Operations capability for R&D. Identify and prioritize AI opportunities, discover workflows, design and deliver AI-native solutions, and manage their lifecycle after launch. Responsibilities include improving enterprise AI tools, coordinating access and governance, evaluating reliability and security, supporting automations and agents, measuring adoption and value, and partnering with Product, Engineering, IT, InfoSec, Finance, and other teams.

Design, build, and scale production AI agents across EveryWatch. Own the agent roadmap, architecture, shared tools, memory, state, observability, evaluation, and cost controls. Harden WatchChat, develop RAG and tool-calling systems, establish measurable quality standards, and ship solutions directly in Python. Collaborate with sales, product, data, and engineering teams to identify high-impact use cases and take agent concepts from discovery through production.

Join Welo Data’s Canadian French contributor network for potential remote AI projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts for large language models; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with compensation and details provided before each assignment.

Join Welo Data’s French AI Trainers Network as a flexible contributor supporting annotation, evaluation, and prompt creation projects. Contributors may label text, images, or audio; assess search results, advertisements, and chatbot responses; create prompts for large language models; and ensure cultural and linguistic accuracy. This is a talent community rather than an active opening, with project details and compensation provided when assignments become available.

Create finished AI-generated video scenes and sequences for short-form scripted mobile dramas. Translate scripts into visual content, combine AI-generated images, video, and audio into coherent stories, and apply storytelling, pacing, composition, and visual structure. Work independently, collaborate with creative leads, deliver complete creative projects, and improve AI production workflows.

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.

Join Welo Data’s remote contributor network for future AI data projects involving text, image, or audio annotation; search, ad, and chatbot evaluation; prompt creation; and cultural or linguistic accuracy review. Contributors must have native or near-native Twi fluency, English proficiency, digital tool comfort, and strong attention to detail. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Freelance remote contributors support AI language-data projects through annotation, evaluation, prompt creation, and Korean-to-Chinese machine-transliterated lyric review. Responsibilities include assessing meaning, fluency, naturalness, and accuracy; rating quality against defined criteria; correcting errors; and providing feedback to improve AI systems. Projects are task-based, flexible, and dependent on availability.

Join Welo Data’s global contributor network for flexible, remote AI data projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts for large language models; and review cultural and linguistic accuracy. Native or near-native Javanese fluency, English proficiency, digital tool familiarity, and attention to detail are required. This is a talent community rather than an active job opening.

Join Welo Data’s global contributor network for flexible, remote AI projects. Depending on skills and availability, contributors may annotate text, images, or audio; evaluate search results, advertisements, or chatbot responses; create prompts for large language models; and assess cultural and linguistic accuracy. Native or near-native Somali fluency, English proficiency, digital tool comfort, attention to detail, and curiosity are required. This is a talent community application, not an active job opening.

Contribute to AI data projects through language data annotation, evaluation, and instruction creation. Work remotely with flexible hours to help develop more inclusive and capable AI systems. Applicants must be native or near-native Simplified Chinese speakers living in China, Canada, the United States, or Malaysia, with fluent English, comfort using digital tools, strong attention to detail, and curiosity.