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.