Top Artificial Intelligence Jobs in Valencia

Advise and support an internal platform team designing, implementing, and operating a secure, scalable AI platform on Azure Databricks. Responsibilities include architecture, MLOps standards, CI/CD/CT pipelines, Terraform infrastructure, governance, security, reliability, code and design reviews, troubleshooting, mentoring, and knowledge transfer. The role requires deep hands-on expertise with Databricks, Azure services, Python, PySpark, Unity Catalog, and production ML platforms.

Own the lifecycle of AI products by translating business priorities into executable roadmaps, partnering with engineering and design, driving delivery, and incorporating user feedback. Lead client demonstrations, define and evaluate product metrics, coordinate cross-functional teams, and align product development with broader innovation strategy. The role requires strong product management, leadership, communication, analytical, agile, and user research skills.

Build Solidgate’s ML/AI function from the ground up, developing real-time payment routing models and production pipelines. Own the full ML lifecycle from experimentation and A/B testing through deployment, while solving modeling challenges involving large-scale transactional data. Partner with Product, Engineering, and Data Platform teams to deliver measurable improvements in conversion, approval rates, losses, and revenue.

Leads OKX’s global marketing compliance function, building policies, controls, review and approval processes, monitoring programs, and regulatory change management for advertising, promotions, social media, influencers, affiliates, and product launches across CeFi and DeFi. Partners with Marketing, Product, Legal, Risk, and Compliance teams; manages incidents, supports audits, delivers training, and scales the compliance team and framework.

Leads research and advisory work for CIOs on data, analytics, and AI strategy, governance, operating models, architecture, value realization, and emerging technologies. Develops thought leadership, market analysis, presentations, and actionable client guidance; evaluates agentic and composite AI, modern data platforms, AI-ready data, organizational maturity, and capability-building needs. Represents Gartner at client meetings and conferences, supports sales, mentors colleagues, and shapes research agendas.

Own post-deployment value, adoption, and expansion for strategic Private Cloud AI customers. Advise customers on enterprise AI, GenAI, agentic AI architectures, roadmaps, use cases, and platform scaling. Lead value reviews, workshops, and onsite engagements; identify expansion opportunities; build technical and commercial value cases; and collaborate with Sales, Product, Engineering, and Support. Develop reusable global playbooks, governance, metrics, and customer engagement processes.

Lead the engineering function on a remote consulting mission by setting technical direction, managing and mentoring engineers, driving the roadmap, overseeing complex delivery, improving engineering practices, and partnering with product and business stakeholders. The role requires hands-on technical leadership, architectural judgment, agile expertise, and evaluation of emerging technologies including cloud, AI, and blockchain.

Lead the engineering function for a growing technology company on a renewable consulting mission. Responsibilities include setting the engineering roadmap, managing and mentoring engineers, guiding architecture and technical decisions, leading complex projects, improving engineering practices, and collaborating with product and business stakeholders. The role requires hands-on technical involvement, strong software engineering expertise, and the ability to evaluate emerging technologies including cloud, AI, and blockchain. French fluency and strong English communication skills are mandatory.

Develop R automation and AI solutions supporting pharmaceutical clinical trials. Interpret requirements, identify workflow improvements, build proof-of-concept tools using R, Shiny, and LLM-supported coding, and mature successful prototypes into validated, documented, reusable solutions. Collaborate with statisticians, programmers, data scientists, and automation leads while ensuring compliance with clinical development standards, including testing, traceability, audit trails, version control, and regulated delivery expectations.

Designs and delivers AI-native solutions across business functions including People, Legal, Finance, and Operations. Responsibilities include identifying transformation opportunities, building and deploying AI agents and automated workflows, integrating enterprise systems, driving adoption, measuring business impact, applying governance and human oversight, and mentoring colleagues. The role partners with functional leaders to redesign operating models and continuously improve production AI solutions.

Own and operate the AI security runtime control plane across Azure, AWS, and GCP. Build inline AI enforcement, tune prompt-injection, data protection, tool-call, and agent access policies, and integrate security platforms with SIEM/SOC workflows. Lead L3 investigations, automated containment, cloud and Kubernetes security, DevSecOps controls, vendor evaluations, and closed-loop red-team remediation. The role requires automation, infrastructure-as-code security, multi-cloud identity management, incident response, and collaboration with technical leadership.

Provides L2 monitoring, triage, investigation, and escalation for AI and cloud security detections. Analyzes telemetry using KQL or SQL, maintains dashboards, and produces operational, compliance, and risk reporting. Investigates AI threats including prompt injection, jailbreaks, data leakage, agent hijacking, and unauthorized tool activity. Monitors Azure, AWS, and GCP posture, supports vulnerability and compliance remediation, documents cases, and partners with SOC, cloud, incident response, and engineering teams.

Architects and delivers enterprise AI, machine learning, generative AI, RAG, and agentic systems. Designs secure end-to-end architectures, integrates Claude and other models with ServiceNow, APIs, databases, cloud platforms, and workflows, and leads discovery, proofs of concept, and client delivery. Develops ML and NLP solutions, data pipelines, dashboards, evaluation frameworks, observability, governance, and responsible AI controls. Collaborates with stakeholders, engineers, consultants, and clients to operationalize reliable AI applications.

Own the architecture and technical direction of the company’s AI platform, including model gateways, routing, agent orchestration, MCP, identity and governance, evaluation, observability, security, and FinOps. Build and operate production services, establish engineering standards and golden paths, partner with Security and Legal, mentor engineers, influence cross-functional decisions, and participate in on-call and incident response.

Build and operate production AI platform services, including gateways, model routing, plugin and MCP review pipelines, observability, evaluations, cost attribution, agent identity, secrets, and security controls. Develop developer tooling and enablement resources, collaborate with Security teams, manage incidents, and participate in on-call support. The role requires strong software, platform, DevOps, or SRE experience with LLM APIs, cloud infrastructure, CI/CD, Kubernetes, Terraform, and observability systems.

Build and operate production AI products using generative AI, LLMs, RAG, vector search, and agentic systems. Develop scalable machine learning services, pipelines, APIs, infrastructure, and automated evaluation systems. Improve AI quality, reliability, security, performance, and cost while establishing engineering standards. Collaborate with Product, Engineering, Data Science, Data Engineering, and Analytics teams to deliver dependable customer experiences.

Lead enterprise Agentforce architecture and hands-on agentic AI engineering for European clients. Design agent workflows, configure Salesforce agents, integrate deterministic Apex and Flow logic, implement LLM orchestration, RAG, APIs, MuleSoft pipelines, security guardrails, and automated testing. Conduct technical discovery, advise enterprise stakeholders, and guide engineering teams through production deployments. This is a fractional, project-based advisory role requiring deep Salesforce architecture and advanced LLM engineering expertise.

Lead Nuitee’s agentic AI strategy and capabilities for searching, booking, paying for, modifying, and canceling hotel stays. The role combines hands-on software engineering, product development, technical leadership, commercial opportunity identification, and team building. Reporting to the CEO, this leader will design secure agent-native APIs and MCP tools, improve transaction reliability, and take new products from concept to production across Nuitee’s travel infrastructure.

Build a model enablement platform for heterogeneous AI computing across AIPUs, CPUs, GPUs, NPUs, and other accelerators. Responsibilities include model ingestion, graph partitioning, compilation, runtime execution, performance profiling, memory and scheduling optimization, large-model offloading, and verification integrated into CI. The role combines architecture ownership with hands-on C++ and Python engineering across model frontends, compilers, runtimes, and application pipelines.

Own LLM and VLM enablement on Axelera AI hardware, from studying and profiling models through productionizing them in the Voyager SDK. Responsibilities include PyTorch references, quantization, weight mapping, model contracts, pipeline integration, KV-cache management, multimodal serving, accuracy validation, and bring-up platform development. The role also shapes GenAI, agent, and speech capabilities for edge devices.

Partner with government customers and partners to design, prototype, and deploy AI solutions (computer vision, LLMs, generative/agentic AI). Create technical collateral, lead hands-on trials and deployments using NVIDIA hardware/software, and advocate product requirements across product, sales, and engineering teams.

Lead the AI architecture for Productboard Insights, designing agent-native systems, context infrastructure, self-healing workflows, evaluation processes, and AI code-review optimization. Own technical direction across Insights, Spark, and platform teams; drive features from concept through beta; optimize quality, latency, cost, and reliability; write production code; and develop engineers through documentation and reviews.

Design, build, and deploy production-grade generative AI assistants and agents using LLMs, RAG, embeddings, vector databases, tool calling, and orchestration. Develop full-stack applications with Python, TypeScript, React, and AWS services including Bedrock and AgentCore. Implement infrastructure as code with Pulumi, integrations through APIs and MCP, security controls, observability, automated evaluation, and performance optimization. Communicate technical decisions to business stakeholders and continuously assess emerging AI technologies.

Design, build, and deploy production-grade generative AI assistants and agents using LLMs, RAG, tool calling, memory, and orchestration. Develop full-stack solutions with Python, TypeScript, React, and AWS services including Bedrock and AgentCore. Build integrations, APIs, authentication, infrastructure as code, observability, evaluation, and cost and latency optimization. Communicate technical decisions to business stakeholders and proactively adapt to emerging AI technologies.

Build AI-powered automation agents and modernize legacy enterprise systems for SME clients. Responsibilities include developing Python backends, integrating Salesforce, SAP, and Microsoft Dynamics, cleaning and transforming messy data, and delivering outputs through Power BI, PDFs, and APIs. The role involves working with LLMs, agent frameworks, and AI coding tools while collaborating with Spanish- and English-speaking clients in a fully remote consultancy environment.