Descripción de la oferta
Principal MLOps Engineer - GenAI Platforms
Location: Remote from Spain (an indefinite Spanish employment contract)
La siguiente información ofrece un resumen de las habilidades, cualidades y cualificaciones necesarias para este puesto.
We are looking for a seasoned MLOps Engineer with strong technology and consulting experience to join the AI/ML Practice team at Intellias. Join us to blueprint GenAI platforms and establish LLMOps practices for client teams across industries, partnering from presales and discovery through PoC to production.
Requirements:
7+ years in MLOps/platform architecture or adjacent roles, with shipped AI systems
Proficient Python and strong software engineering principles
Deep experience with at least one major cloud (AWS/Azure/GCP) and platform engineering (containers, Kubernetes, IaC such as Terraform)
Experience in designing and guiding scalable machine learning pipelines for model training, validation, and deployment
Proven CI/CD design for GenAI/ML (evaluation gates, versioning, canary, rollback) and collaboration with security/governance stakeholders
Sound judgement selecting RAG/vector and provider stacks based on performance, cost, compliance, and portability
Agent orchestration frameworks (e.g., LangGraph/Semantic Kernel) and tooling protocols (e.g., MCP)
Experience operationalizing multi-agent systems (tools/routing/memory/guardrails, human-in-the-loop)
Process automation and enterprise integrations
Excellent communication and interpersonal skills to collaborate effectively with cross-functional teams, stakeholders' leadership
Upper-intermediate level of English
Nice to have:
Master or higher degree in Computer Science, Engineering, or related field
On‑prem LLM deployments; performance and cost tuning with caching and model routing
AI safety, policy, and compliance experience in sensitive environments
Public speaking and enablement and building reusable accelerators
Domain exposure in automotive, retail, manufacturing, healthcare, energy, finance, or telecom
Responsibilities:
Lead discovery with stakeholders and define adoption roadmaps and reference architectures
Set lifecycle practices for GenAI (LLMOps)
Architect retrieval and provider layers (RAG, vector stores, model gateways) with portability, cost, and compliance in mind
Implement RAG/agent workflows that orchestrate tool‑calling, retrieval, and grounded answering
Enable agentic applications at platform level and define solution patterns and evaluation gates (standardized tools, routing, shared memory, HIL, safe fallbacks) aligned with enterprise integration, security, and cost
Set standards for ingestion, chunking, embedding, and indexing pipelines; select and tune vector databases for retrieval
Establish CI/CD, Infrastructure-as-Code, observability, and automated testing
Define governance and safety guardrails
Establish environment strategy and promotion paths, and a clear handover plan to client teams
Package reusable patterns/accelerators, mentor engineers, and support presales and proposals
At Intellias, where technology takes center stage, people always come before processes. We're dedicated to cultivating a tech‑savvy environment that empowers individuals to unlock their true potential and achieve extraordinary results. Our customized benefits not only prioritize your well-being but also charge your professional growth, making this opportunity an ideal match for tech enthusiasts like you.
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