Specialist Computer Centres, S.L. , an English multinational company with a strong presence across Europe, dedicated to the development of projects, deployments, and implementation of IT services, is seeking an AI Automation & Integration Specialist Main Mission The AI Automation & Integration Specialist designs, develops, tests, deploys, secures and operates production-grade automations and integrations that connect business processes, enterprise applications, cloud services, data platforms and AI capabilities. The role is a hands-on senior engineering position within SCC Spain's AI delivery capability, translating solution architectures and business requirements into resilient APIs, event-driven services, automated workflows and reusable integration components across Microsoft Azure and AWS. A core objective is to convert manual, fragmented or repetitive activities into secure, observable and reusable automated processes that deliver measurable operational outcomes. The role ensures that AI-enabled applications and automations are not isolated proofs of concept, but supportable production services that integrate reliably with customer processes and systems. Key Responsibilities Automation Development & Intelligent Process Orchestration

Maintain automation assets throughout their lifecycle, including versioning, testing, deployment, monitoring, incident resolution and continuous optimisation. Refactor proofs of concept and low-code workflows into governed, observable and supportable production services when scale, criticality or complexity requires it. Measure automation outcomes including transaction completion, processing time, failure rate, manual effort avoided, rework and operational cost. Define exception paths, audit trails, manual recovery procedures and operational controls for business-critical automations. Combine deterministic workflow logic with AI capabilities such as classification, extraction, summarisation, routing, decision support and agent tool execution. Automate interactions with Microsoft 365 and enterprise platforms using Microsoft Graph, APIs, webhooks, events, queues and secure workload identities. Build reusable connectors, custom connectors, workflow templates, automation libraries and common services that reduce delivery time across customer projects. Implement scheduled, event-triggered, short-running, long-running and human-in-the-loop workflows, including state management, approvals, timeouts, escalation, compensation and recovery logic. Design, develop, test, deploy and operate end-to-end automations using Azure Functions, AWS Lambda, Logic Apps, Durable Functions, Step Functions, Power Automate and code-based orchestration where appropriate. Analyse business and operational processes to identify automation opportunities, define automation boundaries and translate requirements into maintainable technical workflows.

Cloud-native Integration & Automation Engineering

Design and implement API-first, event-driven and asynchronous integration solutions using Azure Functions or AWS Lambda, Event Grid or EventBridge, Service Bus or SQS/SNS, and workflow orchestration services such as Logic Apps, Durable Functions or Step Functions. Build reusable automation components, connectors and integration services using C#, Python, TypeScript or PowerShell, applying appropriate software engineering standards. Integrate enterprise systems, SaaS platforms, data services and AI endpoints through REST, GraphQL, webhooks,



messaging and event streaming patterns. Modernise legacy point-to-point integrations into loosely coupled, scalable and maintainable cloud-native patterns. Assess and implement synchronous versus asynchronous patterns, delivery semantics, ordering, idempotency, deduplication, dead-letter handling and eventual consistency.

API Management & Enterprise Integration

Design, publish and govern APIs using Azure API Management and AWS API Gateway, including policies, authentication, authorisation, throttling, quotas, versioning, transformations, caching, lifecycle management and developer onboarding. Create and maintain API contracts and documentation using OpenAPI specifications, consistent error models and backward-compatible versioning practices. Integrate with Microsoft 365 services through Microsoft Graph, including appropriate permissions, consent models, webhook subscriptions, change notifications and throttling-aware implementations. Collaborate with architects to define reusable integration reference architectures, standards and guardrails for customer delivery teams.

Identity, Security & Secrets Management

Implement workload identity and zero-trust patterns using Managed Identities, AWS IAM roles, OAuth 2.0 and OpenID Connect, avoiding embedded credentials wherever possible. Protect credentials, certificates, keys and connection details using Azure Key Vault or AWS Secrets Manager, including secure rotation and access-control practices. Apply least privilege, managed service-to-service authentication, network controls, encryption and secure API exposure throughout the integration lifecycle. Contribute to threat modelling, security reviews and remediation of integration components in collaboration with Cyber Security and Cloud teams.

AI-enabled Workflow Integration

Integrate Azure OpenAI, Azure AI Foundry, AWS Bedrock, Microsoft Copilot Studio, AI agents and other model endpoints into enterprise workflows and applications. Engineer the deterministic components around AI systems, including input validation, context retrieval, tool and function calling, business-rule enforcement, human approval, output handling and fallback paths. Implement resilient orchestration for long-running or multi-step AI processes, with appropriate state management, timeout handling, compensation and human-in-the-loop controls. Ensure sensitive data, prompts, model outputs and integration telemetry are handled in accordance with security, privacy and responsible AI requirements.

Observability, Reliability & Operational Excellence

Instrument integrations end to end using Application Insights, Azure Monitor, AWS CloudWatch and OpenTelemetry. Implement distributed tracing, transaction correlation, correlation IDs, structured logging, metrics and actionable alerts across APIs, functions, queues, events and AI dependencies. Design robust error-handling and resilience mechanisms, including retries with backoff and jitter, timeouts, circuit breakers, bulkheads, poison-message handling, dead-letter queues and replay procedures.



Define service-level indicators and operational dashboards covering availability, latency, throughput, error rate, queue depth, dependency health, cost and business transaction completion. Perform production troubleshooting and root-cause analysis across distributed systems, and produce runbooks that enable effective support and incident response.

Infrastructure as Code, CI/CD & Quality Engineering

Provision and configure integration services using Terraform and Bicep, with modular, reusable and environment-aware infrastructure definitions. Build CI/CD pipelines using Azure DevOps or GitHub Actions, incorporating code quality, security scanning, automated tests, deployment approvals and rollback strategies. Implement unit, contract, integration, end-to-end, performance, resilience and failure-mode testing for APIs, workflows and event-driven components. Use source control, peer review, branching and release-management practices appropriate to enterprise delivery. Optimise solutions for scalability, reliability, maintainability, performance and cloud cost.

Agile Delivery, Documentation & Continuous Improvement

Work with Product Owners, Architects, Testers, Cloud Developers, AI Engineers and service teams to deliver product increments against agreed sprint goals. Produce clear technical documentation covering APIs, events, message schemas, data flows, identity, deployment, observability, support and recovery procedures. Create proofs of concept and technical spikes to validate patterns, while ensuring successful patterns can be hardened for production use. Mentor colleagues, review technical work and contribute reusable accelerators, standards and lessons learned to the wider AI and application practice.

Required Experience

5 years of professional experience in software engineering, systems integration, cloud application development or automation, including at least 2 years delivering cloud-native integrations in production. Demonstrable experience developing end-to-end business process automations, rather than only configuring integration platforms or defining architectures. Demonstrable hands-on delivery of APIs, serverless components, messaging solutions and event-driven architectures on Azure or AWS. Experience operating distributed integrations in production, including troubleshooting, performance analysis, resilience engineering and support handover. Experience working in Agile delivery teams and collaborating with architecture, security, test, data and operations functions. Fluent Spanish and professional working proficiency in English.

Preferred Qualifications

Experience in an IT services, systems integrator, managed services or consulting environment. Relevant certifications such as Azure Developer Associate, Azure Solutions Architect Expert, Azure DevOps Engineer Expert, AWS Developer or Solutions Architect, and HashiCorp Terraform Associate. Experience with containers, Kubernetes, Dapr, Kafka or enterprise integration platforms is advantageous. Experience delivering solutions for regulated or security-sensitive customers is advantageous. Bachelor's degree or equivalent practical experience in computer science, software engineering or a related discipline.

Working Conditions & Package

Hybrid working model, with Madrid preferred and flexibility to work from SCC Spain offices as required. Travel within Spain for customer delivery, workshops and collaboration with SCC teams.

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📌 AI Automation & Integration Specialist (Madrid)
🏢 remoteo
📍 Madrid