Top Artificial Intelligence Jobs in Seville

Own and deliver product features across trading, investing, crypto, accounts, and payments. Responsibilities include prioritizing features, interpreting regulations and API documentation, writing detailed specifications, coordinating with Engineering, Design, Legal, Compliance, and Operations, leading testing and launches, and monitoring performance after release. Candidates must have shipped products or features, understand technical systems and data flows, query and explain product data, and regularly use AI in product work.

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.

Fine-tune and post-train open-weight LLMs using methods such as SFT, LoRA, QLoRA, DPO, and GRPO. Build training data and evaluations, diagnose model failures, improve personalization and multilingual behavior, accelerate reproducible training workflows, and deploy models to production. The role involves using real user behavior to guide iterations across a large-scale AI companionship platform, with collaboration across AI, product, web, DevOps, and leadership teams.

Build modular, configuration-driven AI video pipelines for mobile gaming advertisements. Integrate generative image, video, text-to-speech, and talking-head models through fal.ai, orchestrate reliable asynchronous jobs, and prevent duplicate generation costs with retries and resumable execution. Use FFmpeg to assemble clips, add subtitles, overlays, audio, and calls to action in multiple aspect ratios. Document workflows so marketing teams can operate them without coding and collaborate with creative specialists.

Lead technical delivery of an AI-assisted operations platform from discovery through implementation and evaluation. Establish technical baselines, validate integrations, design maintainable rules and AI workflows, guide engineers, review code, implement testing and observability, and ensure traceable human-approved decisions. The role requires hands-on architecture, API integration, evaluation, CI, production readiness, and clear communication with business and engineering stakeholders. Travel to an in-person working session in Milan is included.

Lead the architecture and implementation of AI-native product engineering systems, including agent-ready code standards, context infrastructure, self-healing incident workflows, multi-step agentic features, and AI code-review optimization. Ship end-to-end product features, set technical direction, evaluate LLM reliability and trade-offs, and accelerate validated learning through close collaboration with engineering, product, and design teams.

Lead the architecture and implementation of AI-native product engineering systems, including agent-ready code standards, context infrastructure, self-healing incident workflows, multi-step agentic features, and AI code-review optimization. Ship production software, establish technical direction, and partner with product and design teams to accelerate validated learning. The role requires strong backend and distributed-systems expertise, hands-on LLM product experience, and practical use of AI coding tools.

Join Welo Data’s Swahili contributor network for potential remote AI projects involving text, image, or audio annotation; search, advertising, or chatbot evaluation; prompt creation; and cultural and linguistic accuracy review. Applicants must be native or near-native Swahili speakers based in Kenya, Tanzania, or the Democratic Republic of Congo, with English proficiency, digital-tool comfort, and strong attention to detail. Projects vary in duration and compensation, with details provided before participation.

Develop AI-driven products through hands-on software development and product engineering. Build minimum viable products, solve problems creatively, and help shape future AI applications. The role is available remotely or in Boston and Chicago, with contract options ranging from two weeks to three months or full-time, plus potential revenue sharing.

Own the Vault product roadmap and lifecycle for a sports media asset platform. Lead discovery with customers, define solutions for content ingest, storage, integrations, AI enrichment, metadata, search, rights, and asset monetization. Partner closely with engineering, sales, and customer success, attend customer events, and prioritize product bets that help sports organizations maximize the value of extensive media archives.

Own daily operations and quality assurance for an internal AI-powered growth platform. Test releases, rule changes, edge cases, and regressions; document and verify bug fixes; monitor platform and agent activity; manage approval queues; evaluate agent output; escalate risks; and maintain test plans, QA checklists, runbooks, and release notes.

Optimize LLM inference on modern GPUs by analyzing GPU execution, memory access, kernel performance, and system bottlenecks. Develop, debug, reverse-engineer, and optimize CUDA kernels and low-level GPU operations for matrix multiplication, attention, and neural network layers. Benchmark latency, throughput, and GPU utilization while working with inference frameworks such as vLLM, SGLang, TensorRT-LLM, Triton, and FlashAttention.

Build and productionize machine learning systems for classification, retrieval, ranking, personalization, and evaluation. Develop models and datasets, optimize accuracy, latency, cost, and reliability, and maintain training, inference, and deployment pipelines. Monitor production performance, debug issues, and ship improvements based on real-world feedback. Collaborate with engineering and product teams to deliver reliable AI-powered features.

Leads social media and content strategy across markets, owning editorial planning, content distribution, creator programs, community management, and performance analytics. Builds and operates AI-enabled content workflows, coordinates agencies and creators, and turns audience and channel data into measurable demand-generation decisions. Partners with brand, product marketing, performance, and country teams to scale platform-native content across TikTok, YouTube, Meta, and LinkedIn.

Designs and owns global digital marketing strategies across acquisition and customer expansion. Responsibilities include campaign architecture, paid media, ABM, nurture, conversion optimization, regional localization, budget allocation, performance analysis, marketing technology improvements, data hygiene, and AI-enabled campaign operations. The role makes commercial trade-off decisions to maximize pipeline and expansion revenue, collaborates with sales and creative teams, and defines account-level measurement frameworks.

Leads the GTM Systems function, owning the commercial technology stack, AI operating model, vendor lifecycle, systems roadmap, and adoption strategy. Manages five senior individual contributors across Salesforce, marketing/BDR, customer success systems, and web operations. Partners with executive stakeholders to identify automation opportunities, build reliable AI agents, measure business impact, and drive cross-functional change across the revenue organization.

Lead Kraken Pro’s social media strategy across X, Telegram, and other platforms. Create platform-native content, react quickly to crypto and trading trends, manage the content calendar, engage the community, translate product updates into compelling narratives, track performance, and optimize through experimentation. Partner with Legal and Communications to ensure accurate, compliant messaging across regions.

Lead and scale an AI-driven creative design team producing static advertising assets, photorealistic AI visuals, and video source materials. Own creative direction, production workflows, capacity planning, quality control, testing, performance analysis, and AI tooling research. Collaborate with marketers, media buyers, copywriters, producers, video editors, and engineering to develop high-performing paid-media creatives and scalable prompt, style, and automation systems.

Build and lead n8n’s internal AI and automation enablement function. Run recurring workshops, office hours, build-alongs, bounty hunts, hackathons, and dogfooding initiatives for technical and non-technical teams. Develop reusable templates, measure AI fluency and adoption, support cross-functional champions, and act as product owner for a safe internal automation playground. Partner with IT, Security, Data, and Solutions Engineering to define access, credential, and environment requirements.

Evaluate AI-generated customer service and technical responses for clarity, usefulness, natural language, technical accuracy, JSON validity, formatting, and guideline adherence. Provide clear feedback explaining evaluation decisions. The role requires multilingual fluency, coding knowledge, strong written communication, attention to detail, and consistent judgment. Experience with AI evaluation, quality assurance, APIs, structured data, customer service, software development, or technical writing is preferred.

Supports Account Executives throughout the sales cycle by leading technical discovery, solution design, demonstrations, workshops, proofs of concept, evaluations, and technical validation. Translates engineering, simulation, HPC, AI, and infrastructure requirements into Rescale recommendations, documents opportunities in Salesforce, resolves technical risks, supports negotiations, and ensures effective post-sale handoffs across Northern Europe.

Develop and enhance a live drive-thru Voice AI product through software engineering, AI/LLM prototyping and fine-tuning, conversation analysis, system integrations, and customer requirements gathering. Build, test, deploy, and improve production features while evaluating real dialogs and collaborating with customers and internal stakeholders.

Lead applied research and system design for agent-native search: build multi-stage retrieval, ranking, and grounding methods for LLM-driven, iterative agent workflows; deploy high-throughput, low-latency production systems; define evaluation metrics; run experiments and mentor engineers.

Build and enhance RAG systems, AI components, backend services, data pipelines, and REST APIs under senior guidance. Write production code, tests, evaluation harnesses, documentation, and runbooks. Support AWS deployments using containers and CI/CD, investigate model failures, and contribute to architecture and client handovers. The role offers increasing ownership of technical components and decisions while working in distributed, customer-facing delivery teams.

Design, implement, and optimize high-performance attention and foundational AI kernels for GPUs, NPUs, ASICs, and other accelerators. Build reusable attention-framework abstractions, profile workloads, develop benchmarks and correctness tests, analyze hardware and compiler behavior, and improve production inference performance. Collaborate with hardware and software teams, document designs, resolve ambiguous performance issues, and mentor engineers while supporting new accelerator architectures and AI workloads.