Top Artificial Intelligence Jobs in Valencia

Build and own AI models, data pipelines, evaluation suites, and AI product features for construction procurement software. Develop document extraction and workflow automation using generative AI, LLMs, RAG, and optimization algorithms. Design complex data models, integrations, backend services, and production systems using Go, GraphQL, PostgreSQL, and AWS.

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 Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Owns end-to-end product and operational analytics for AI-powered and conventional automation features. Responsibilities include experiment design, funnel and adoption analysis, AI output evaluation, hallucination and failure investigation, monitoring, dashboards, and measuring business impact. The role partners with Product, Engineering, Clinical, MedOps, and Legal, using SQL and Python to analyze messy production data and translate findings into decisions.

Build and operate production AI services, including multi-agent systems, LLM pipelines, MCP servers, RAG and document-ingestion workflows. Develop reliable Python backend services, evaluate model quality, manage deployments, observability, authentication and privacy safeguards. Collaborate with engineering and product teams while supporting AI governance, risk documentation and ISO evidence. The role focuses on practical business automation across document processing, customer support, CRM and account operations.

Owns full-cycle recruiting for commercial, operational, and technical roles across global markets. Responsibilities include sourcing passive candidates, building pipelines for hard-to-fill positions, advising hiring leaders, coordinating interviews and offers, maintaining accurate Greenhouse data, and improving hiring processes through systems thinking, data, AI, and automation.

Lead strategy and execution for early-stage generative and agentic AI products supporting clinical trial workflows. Define product vision, roadmaps, requirements, priorities, KPIs, and experimentation plans. Partner with clinical, operational, AI, and engineering stakeholders to identify use cases, accelerate adoption, and scale successful initiatives. Evaluate investments, guide rapid prototypes, and drive measurable improvements in trial speed, quality, and cost efficiency.

Build BLP’s core software across infrastructure, backend, machine learning, and product extension platforms. Responsibilities include operating secure and observable cloud infrastructure, developing performant distributed systems, applying AI to business problems, and enabling customer process automation. The role emphasizes formal reasoning, correctness by construction, maintainable systems, type systems, and functional programming. Work is available onsite in Zurich or remotely within Europe.

Build and operate production AI infrastructure powering intelligent agents at scale. Develop high-performance Rust services for model inference, orchestration, and execution; design scalable distributed systems; establish MLOps, observability, guardrails, and failure recovery; and optimize latency, throughput, reliability, and cost. Partner with agent systems and infrastructure teams to turn prototypes into hardened services serving millions of users.

Serve as the senior technical expert for EMEA AI organizations training and post-training large-scale foundation models. Advise customers on distributed training infrastructure, PyTorch, Megatron-LM, NeMo, reinforcement learning, GPU utilization, communication overlap, and memory management. Build strategic technical relationships, translate customer needs into NVIDIA product roadmap input, collaborate with research and product teams, and support hackathons, demonstrations, and technical conferences.

Build and deploy reliable, measurable, and safe AI agents for real business workflows. Work within Marketing Engineering and growth pods to identify problems, develop end-to-end solutions, evaluate LLM performance, and measure business impact. The role involves productionizing agent systems beyond demos, using Python, SQL, LLM APIs, and orchestration tools, with potential integration into go-to-market data and marketing systems.

Conduct research, market sizing, forecasting, competitive analysis, and thought leadership on enterprise AI services. Develop actionable insights for technology providers and senior executives through published research, presentations, conferences, and client engagements. Assess market trends, demand drivers, customer behavior, and growth opportunities while advising clients, supporting sales, reviewing content, mentoring analysts, and improving research processes.

Leads end-to-end architecture for enterprise data, analytics, and AI solutions in a Microsoft-first environment. Translates business requirements into secure, scalable designs and guides prototyping, implementation, architecture reviews, troubleshooting, governance, and production readiness. Requires deep hands-on experience with Azure data platforms, Power BI, enterprise security, Azure OpenAI, and retrieval-augmented generation patterns.

Lead the strategy and roadmap for Wrike’s AI Platform and Ecosystem, including MCP, Skills, and GraphQL. Direct the core MCP team, establish standards for agent-facing tools, guide GraphQL product evolution, and manage plugin distribution across AI marketplaces. Partner with engineering, architecture, security, customers, and product teams to improve reliability, governance, permissions, documentation, developer experience, and agent workflows. Use customer research, adoption data, experiments, and ecosystem feedback to prioritize outcomes.

Manage influencer campaigns end to end across multiple brands and markets. Responsibilities include creator casting, briefing, negotiation, contracting, campaign timelines, budgets, approvals, client communications, performance tracking, reporting, and optimization. The role requires using CPV and campaign KPIs to manage commercial outcomes, ensuring content meets brand and compliance requirements, and operating as a power user of Kyra’s platform and AI tools.

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.