PAI Consultant /ppLocation: Remote from Spain (an indefinite Spanish employment contract) /ppbr/ppbr/ppOur client is the fastest-growing global manufacturing company. An international corporation with over a hundred years of history, internationally recognized brands and Reduced-Risk Products. /ppIntellias' mission is to support its strategy and efforts in the Digital and e-commerce space (e-commerce and other apps mobile apps, payment gateways, loyalty system, search engine, employee management, identity management, etc.). /ppA newly conceptualized Digital Eco System is comprised of a set of capabilities including an online shop website, linking online offline, customization personalization, engagement membership, digital product services main differences. /ppbRequirements: /b /pulli5+ years in MLOps/platform architecture or adjacent roles, with shipped AI systems /liliProficient Python and strong software engineering principles /liliDeep experience with at least one major cloud (AWS/Azure/GCP) and platform engineering (containers, Kubernetes, IaC such as Terraform) /liliExperience in designing and guiding scalable machine learning pipelines for model training, validation, and deployment /liliProven CI/CD design for GenAI/ML (evaluation gates, versioning, canary, rollback) and collaboration with security/governance stakeholders /liliSound judgement selecting RAG/vector and provider stacks based on performance, cost, compliance, and portability /liliAgent orchestration frameworks (e.g., LangGraph/Semantic Kernel) and tooling protocols (e.g., MCP) /liliExperience operationalizing multi-agent systems (tools/routing/memory/guardrails, human-in-the-loop) /liliProcess automation and enterprise integrations /liliExcellent communication and interpersonal skills to collaborate effectively with cross-functional teams, stakeholders' leadership /liliUpper-intermediate level of English /li /ulpbNice to have: /b /pulliMaster or higher degree in Computer Science, Engineering, or related field /liliOn-prem LLM deployments; performance and cost tuning with caching and model routing /liliAI safety, policy, and compliance experience in sensitive environments /liliPublic speaking and enablement and building reusable accelerators /liliDomain exposure in automotive, retail, manufacturing, healthcare, energy, finance, or telecom /li /ulpbResponsibilities: /b /ppb1. Architecture Review Production Readiness Assessment /b /ppb• /b Evaluate AI/ML and LLM solution architectures to ensure they are scalable, secure, and aligned with enterprise patterns. /ppb• /b Assess MLOps/LLMOps pipelines, model serving infrastructure, data flows, and integration points. /ppb• /b Identify architectural risks or gaps and propose mitigation strategies. /ppb2. Compliance Standards Validation /b /ppb• /b Verify that all AI development activities follow JTI’s internal development standards, documentation rules, and operational guidelines. /ppb• /b Ensure compliance with model governance, lifecycle management, versioning, and traceability requirements. /ppb• /b Check adherence to security, privacy, and data handling policies. /ppb3. Technical Quality Assurance /b /ppb• /b Perform in‑depth technical code reviews, configuration reviews, and environment checks. /ppb• /b Validate model performance metrics, evaluation methodology, drift controls, and monitoring strategies. /ppb• /b Review model explainability, responsible‑AI controls, and risk assessment outputs. /ppb4. Pre‑Deployment Validation /b /ppb• /b Conduct formal readiness reviews before solutions are promoted to production. /ppb• /b Provide clear recommendations for required fixes, improvements, or optimization. /ppb• /b Approve or block deployment based on technical quality and compliance. /ppb5. Documentation Reporting /b /ppb• /b Produce detailed review reports summarizing findings, gaps, and actionable guidance. /ppb• /b Maintain traceability of assessments across multiple projects throughout 2026. /ppb6. Cross‑Team Collaboration /b /ppb• /b Collaborate with engineering, data science, architecture, and product teams to clarify requirements and ensure alignment. /ppb• /b Participate in technical workshops and solution walkthroughs. /ppb7. Advisory Best Practices Enablement /b /ppb• /b Advise teams on AI/ML and LLM best practices, including architecture, operations, MLOps, evaluation, and productionization. /ppb• /b Help standardize review processes and improve internal frameworks when needed. /p