Top Remote Jobs in Portugal

Build and maintain agentic AI platform capabilities, execution environments, workload orchestration, and software integrations. Deploy and optimize computer vision models, LLM services, and inference infrastructure on accelerated hardware. Validate platform correctness, performance, security, reliability, and failure recovery across software and compute layers. Produce documentation and operational runbooks while collaborating across teams and adopting unfamiliar tools and systems.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

Own lifecycle engagement for a digital obesity and lifestyle support programme, managing activation, education, retention, reactivation, referrals, automated campaigns, segmentation, experimentation, and funnel optimization. Partner with Product, Analytics, Medical, Legal, Compliance, and healthcare organizations to deliver accurate, compliant communications across markets. The role also supports lifecycle initiatives for the core app.

Build and own the architecture for Dune’s curated data lifecycle, including dependency-aware orchestration, backfills, schema evolution, retries, recovery, data quality, and alerting. The role combines backend software engineering with large-scale data systems work across Go, Kotlin, Rust, Python, and SQL. Responsibilities include designing ingestion and curation contracts, making architecture decisions, solving ambiguous problems, and leading work that other engineers can execute.

Provide technical customer support for Ashby by diagnosing integration and API issues, troubleshooting via logs and scripting, collaborating with engineering on escalations, creating documentation, and driving product improvements from customer feedback.

Own the full enterprise customer journey from kickoff through adoption and ongoing value realization. Build executive and technical stakeholder relationships, lead QBRs and EBRs, translate product performance into business outcomes, manage risks and escalations, provide strategic ecommerce recommendations, maintain success plans, and partner with Account Management on retention and expansion.

Prospect and acquire restaurant and hotel clients across Spain and Portugal through phone, email, WhatsApp, events, and field outreach. Demonstrate CentralApp’s SaaS platform, manage territory performance, collaborate through onboarding, support local partners, gather market insights, and represent the company in the regional market.

Lead a 3–5-person B2B telesales hunting team in Lisbon, driving new corporate-client acquisition and onboarding. Develop outbound sales strategies, monitor KPIs, manage pipelines, coach agents, analyze market and competitor trends, and improve telephone sales performance. Use Genesys, Salesforce, AWS, and AI tools to increase productivity and visibility. The role also contributes to strategic decisions and expansion plans while requiring fluent French and English.

Build, maintain, and improve C#/.NET backend services, REST APIs, enterprise integrations, and SQL-based workflows. Troubleshoot production issues, technical debt, data problems, and integration failures across Microsoft Dynamics GP, Odoo, Azure, and related platforms. Collaborate with technical and business stakeholders, document system behavior, improve reliability and performance, learn evolving enterprise technologies, and participate in interviewing future team members.

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.