€600 - €800
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91,000+ live jobsSenior Engineer - Agentic Platform and AgentOps
Hybrid in Madrid·Added 11 days ago (last checked 22 Oct)
Our summary
- Hours
- Jornada intensiva in summer
- Work mode
- Hybrid, Madrid
- Experience
- Senior level
- Benefits
- Private health insurance, life insurance, flexible pay plan, gym access




Visa options
The ad doesn’t mention sponsorship
Not a refusal, but not a yes. Worth asking in your first message.
Skills
This job advert was originally written in Spanish.
Requirements
What we're looking for
- AgentOps / LLMOps - Expert: Lifecycle, operation, evaluation, observability, security, and continuous improvement.
- Generative AI and agents - High: Agents, sub-agents, RAG, memory, tools, function calling, MCP, and orchestration.
- Multicloud - High: Azure, AWS, and GCP; runtimes, identity, networks, secrets, containers, and resilience.
- Observability - Expert: OpenTelemetry, metrics, logs, traces, dashboards, alerts, and SLOs.
- DevOps and IaC - High: GitHub, CI/CD, Terraform, deployments, policy as code, and configuration.
- AI Security - High: Identity, least privilege, DLP, guardrails, auditing, secrets, and response.
- Python - Solid: SDKs, automation, integrations, evaluation, and operational tooling.
- Experience building or operating generative AI platforms or agents in enterprise and regulated environments.
- Real production experience: incidents, performance, security, continuity, scaling, and continuous improvement.
- Integration with identity, secrets, network, observability, ticketing, CMDB/inventory, and change management.
- Working with Architecture, Security, AI Center, Operations, Data, Engineering Platform, and products.
- Ability to make decisions, manage risks, and convert repeated needs into platform capabilities.
Nice to have
- LangGraph, ADK, Semantic Kernel, LangChain, or other orchestration patterns.
- Microsoft Agent 365, Copilot Studio, Azure AI Foundry, AWS Bedrock/AgentCore, and GCP Vertex AI.
- LLM Gateway, model selection, quotas, fallback, and multiple providers.
- MCP, APIs, and tools: registration, authorization, versioning, timeouts, circuit breakers, and traceability.
- Offline and online evaluation, test sets, prompt regression, and acceptance criteria.
- Metrics for groundedness, relevance, completeness, security, hallucination, and task success.
- Detection of drift in prompts, models, data, tools, and behavior.
- Versioning of prompts, configurations, models, archetypes, tools, and policies.
- OpenTelemetry and end-to-end correlation of conversations, sub-agents, LLMs, MCPs, APIs, and dependencies.
- Dashboards with p50/p95/p99, error rate, throughput, uptime, tool success rate, retries, and consumption.
- Runbooks, actionable alerts, on-call, post-mortem, and remediation automation.
- Continuity: retry, fallback, controlled degradation, restore, rollback, and DR.
- Workload identities, Entra ID/IAM, RBAC/ABAC, least privilege, segregation, and Just-in-Time access.
- DLP, classification, encryption, retention, and control of knowledge and memory.
- Guardrails against prompt injection, tool abuse, and exfiltration.
- Kill switch, safe-stop, quarantine, evidence, and coordination with Security.
- Cost per agent, model, provider, product, and organizational unit.
- Quotas, budgets, limits, alerts, and capacity planning.
- Balance between quality, latency, availability, and cost.
- Technical leadership and judgment to prioritize reliability, security, and value.
- Clear communication with technical, operational, security, and business profiles.
- Platform thinking, standardization, reuse, and product orientation.
- Autonomy, pragmatism, and execution in environments with complex dependencies.
- Mentoring, documentation, and knowledge transfer.
- Certifications in Azure AI, AWS Generative AI, Google Cloud AI, Kubernetes, SRE, or security.
- Dynatrace, Application Insights, Event Hubs, ActiveGate, Purview, Defender, and Microsoft Graph.
- Langfuse, Arize, MLflow, agent evaluation, distributed tracing, and prompt regression.
- Kubernetes, Azure Container Apps, AWS ECS/Fargate, OpenShift, networks, proxies, TLS, and API gateways.
- Responsible AI and frameworks such as NIST AI RMF, ISO/IEC 42001, or applicable European regulation.
Pay & benefits
What you'll get
- Flexible working hours and hybrid work (3 days in the office and 2 days remote).
- A flexible compensation package that includes: meal vouchers, childcare vouchers, medical insurance, life insurance, employee discounts, and more. And if you live in Madrid, a company shuttle bus is available to get you to the office.
- Access to an attractive pension plan.
- Summer intensive schedule.
- You'll be in charge of your own learning journey, with access to thousands of resources to keep advancing your technical expertise. Plus, you'll receive an additional €1,100 per year to further develop your skills.
- 25 vacation days per year (you would receive the proportional days starting from your start date).
- Additionally, at Mapfre we do not work on December 24, December 31, or January 5.
- 28 hours per year for personal matters + 3 recoverable days during Easter week.
- The opportunity to participate in volunteer projects.
- Free paddle tennis courts and gym.
- A great place to work! We're ranked among the 50 best companies to work for in Spain according to Forbes magazine.
We are diverse, and that makes us unique!
The role
Give your career a fresh start and keep growing professionally at Mapfre Tech! You'll join an international environment where you can innovate by working on global projects focused on the latest technology trends. All of this in a flexible, agile setting surrounded by excellent professionals from around the world... Are you ready?
The purpose of the role is to ensure that our Agentic Platform evolves and operates in a reliable, secure, observable, and governed manner, industrializing the agent lifecycle through AgentOps, automation, and Production Ready criteria.
- Direct impact on a transversal platform for multiple countries, products, and teams.
- Real ownership over operational architecture, automation, technical governance, reliability, and roadmap.
- Cutting-edge challenges in multicloud agents, observability, AI security, evaluation, FinOps, and 24x7 operation.
- Opportunity to build the standards that will define how agents are brought into production.
What you'll do
We are looking for a very hands-on Senior Engineer who will technically lead the evolution and operation of the Agentic Platform. Their goal will be to take AI agents from experimentation to industrial, secure, and governed operation, applying AgentOps practices in the same way that DevOps industrializes software.
You will work on a multicloud and multi-framework ecosystem that may include Microsoft 365 agents, Copilot Studio, Azure AI Foundry, AWS Bedrock and AgentCore, GCP Vertex AI, LangGraph, ADK, Semantic Kernel, MCPs, containers, and shared corporate services. You will collaborate with Engineering Platform, Architecture, Security, AI Center, Operations, Observability, FinOps, and product teams.
Your mission will be to guarantee that the Agentic Platform is a reliable and scalable corporate capability, with a clear operating model, unique catalog and inventory, security controls, end-to-end observability, continuous evaluation, cost management, and secure mechanisms for isolation, rollback, and decommissioning.
- Assume technical reference and operational ownership of the Agentic Platform, defining priorities, standards, roadmap, and evolution model.
- Design and maintain the end-to-end AgentOps cycle: provisioning, validation, deployment, evaluation, publication, monitoring, change, suspension, reactivation, rollback, and decommissioning.
- Define and automate the Production Ready Gate so that no agent reaches production without an owner, criticality, technical identity, permissions, telemetry, SLOs, runbooks, continuity, and approval.
- Operate and evolve runtimes, LLM Gateway, MCP servers, catalogs, marketplace, identity, secrets, connectivity, containers, telemetry, and evaluation mechanisms.
- Build unified observability with metrics, logs, and traces for latency, errors, sessions, tool calls, retries, drift, quality, token consumption, quotas, and cost.
- Define alerts, dashboards, and runbooks for the Operations Center, including kill switch or safe-stop procedures with evidence preservation.
- Industrialize deployments through GitHub, CI/CD, infrastructure as code, automated testing, policy as code, and remediation automation.
- Integrate inventory and governance with OneInventory, Entra ID, Purview, Defender, Microsoft Graph, and equivalent services.
- Coordinate advanced troubleshooting and root cause analysis, converting incidents into preventive controls and reusable automations.
- Measure KPIs for availability, reliability, adoption, security, quality, cost, Production Ready, and operational efficiency.
- A platform ready to host and operate critical enterprise agents homogeneously.
- A reliable inventory with functional and technical owners, criticality, identity, dependencies, data, permissions, and environment.
- Sufficient telemetry to detect degradations and reconstruct relevant executions.
- Reduction of MTTR through runbooks, automated diagnosis, and controlled remediation.
- Control of consumption and costs by agent, model, provider, country, product, and use case.
- Auditable traceability of the lifecycle, changes, access, and actions on tools.
1. Discover and inventory: Agents, owners, identities, dependencies, data, tools, criticality, and environment.
2. Validate Production Ready: Architecture, security, telemetry, SLOs, runbooks, continuity, costs, and approvals.
3. Deploy with control: CI/CD, IaC, testing, versioning, environment segregation, and change evidence.
4. Observe and operate: Health, performance, quality, security, usage, and cost; response via runbooks.
5. Improve or retire: Remediation, drift correction, optimization, rollback, or traceable decommissioning.
Where are we?
Las Tablas, Madrid.
Hiring process
First point of contact
With recruitment team
Starts from your application, LinkedIn, or a call from the recruitment team or a partner agency; a first conversation about you and the open opportunities.
Interview with Human Resources
With HR team
Conversation about your interests, experience, skills and how you approach challenges, plus your questions about Mapfre.
Technical interview
With the team · 1–2 sessions
One or two interviews with the team to assess technical skills and explain the day-to-day of the role.
About Mapfre
Mapfre is a global insurance company headquartered in Madrid, Spain, with a strong presence in the insurance and reinsurance markets across Europe, the Americas, and Asia. It offers a wide range of products including life, health, auto, and home insurance, and operates through multiple brands such as Verti. With over 30,000 employees worldwide, Mapfre is one of the largest Spanish multinationals in the insurance sector.
In Spain, Mapfre has its main offices in Madrid and Barcelona, with a significant network of commercial offices across the country. The company is known for its strong corporate culture, focus on digital transformation, and investment in technology and data analytics. For international professionals, Mapfre offers opportunities in areas like data science, cybersecurity, cloud architecture, and finance, with a work environment that values innovation and professional development.
- Industry
- Insurance
- Founded
- 1933
- Employees
- 10,000–50,000
- Headquarters
- Madrid, Spain
- In Spain
- Madrid, Barcelona
Good to know if you are moving
- Mapfre is headquartered in Madrid, Spain, and has a large presence in Barcelona and other Spanish cities.
- The company offers roles in English and Spanish, with many technical positions in data, cloud, and cybersecurity.
- Mapfre has a strong commitment to digital transformation, investing in AI, data analytics, and cloud infrastructure.
- International hires may find opportunities in the company's global operations, especially in Latin America and Europe.
- The company provides a stable work environment with a focus on long-term career development.
In their own words
Additional information
All selection processes at Mapfre are conducted under the principle of EQUAL OPPORTUNITIES and NON-DISCRIMINATION, with the APTITUDES and PERSONAL AND PROFESSIONAL MERIT of the candidate being the criteria on which the final selection for the position is based.
We create work environments that value diversity and are free from discrimination based on sex, race, ideology, religion, sexual orientation, age, nationality, disability, or any other personal, physical, or social condition.
You can consult our Diversity and Equal Opportunity policy: politica-de-diversidad-e-igualdad-de-oportunidades.pdf (mapfre.com)
By applying to this job offer, you are informed and consent to the processing by Mapfre of the personal data you have voluntarily provided through this platform. If you provide personal data of third parties other than yourself, you guarantee that you have obtained and have their prior consent to share their data and that you have informed them accordingly.
Mapfre, as the data controller, will process your data solely for the purpose of managing your participation in selection processes, for which profiles may be created and automated decisions may result from the processing of your data. In order to manage your participation in various selection processes within Mapfre Group companies, subsidiaries, investees, and Fundación Mapfre, your data may be shared with these entities and may be subject to international transfer.
You can consult additional data protection information at MAPFRE in https://www.mapfre.com/corporativo-es/clausulas/RRHHseleccion.pdf where we indicate where to exercise your rights of access, rectification, erasure, restriction, objection, and portability of your personal data.
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