Solution Architect, Ai Sdlc

Intellias
A Coruña, Spain
17 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience required
5 years minimum
Working hours
Regular working hours
Languages
Spanish

Tech stack

Artificial Intelligence Amazon Web Services Application Integration Architecture Microsoft Azure Behavior-Driven Development Cloud Engineering Code Generation Continuous Integration Distributed Systems Knowledge-Based Systems Machine Learning Systems Development Life Cycle
+15 more
Software Engineering Systems Integration Test-Driven Development (TDD) Retrieval-Augmented Generation Large Language Models Prompt Engineering Agentic-AI Event Driven Architecture Kubernetes Information Technology Machine Learning Operations Virtual Agents Domain Driven Design Devsecops Microservices

Job description

Location: Remote from Spain (an indefinite Spanish employment contract)The Principal Engineer is the foremost technical authority for AI-driven software delivery practices. The role defines engineering strategy, architecture standards, AI governance implementation, and enterprise-scale adoption of AI throughout the software development lifecycle. This individual drives transformation towards AI-native engineering practices while ensuring security, quality, traceability, and compliance. Inspired by emerging AI-DLC practices, the Principal Engineer guides teams in leveraging AI across requirements, design, development, testing, deployment, and operationsAbout the ClientOur client is a large global enterprise operating across multiple markets, with a complex technology landscape and a strong focus on digital transformation and innovation. The organization is actively investing in modern cloud, data, and AI capabilities to enable scalable, secure, and highly automated solutions across its business.About the ProjectThe project is focused on building an enterprise-grade AI Agent Platform from the ground up. The platform will provide a standardized foundation for developing, deploying, orchestrating, securing, and observing AI agents across multiple teams and use cases.The initiative covers the full agent lifecycle and brings together agent orchestration, observability, security, governance, integrations, evaluation, and platform engineering. Engineers joining the project will have an opportunity to influence key architectural and technical decisions and contribute to a new platform rather than maintaining an existing solution.Requirements:Bachelor’s or Master’s degree in Computer Science, Engineering, AI, or equivalent experience.12+ years of software engineering experience.5+ years leading architecture or platform engineering initiatives.Deep expertise in cloud-native architecture and distributed systems.Strong understanding of modern AI/ML technologies, LLMs, agent frameworks, RAG, vector databases, and MLOps.Technical ExpertiseLLM orchestrationRAG and knowledge systemsCI/CD and DevSecOpsAI governance frameworksMicroservices and event-driven architecturesKubernetes and cloud platforms (Azure/AWS/GCP)Strategic technical leadershipExecutive communicationSystems thinkingMentorship and coachingResponsibilities:Technical LeadershipDefine enterprise architecture and engineering standards for AI-enabled development.Create frameworks, reference architectures, and reusable platform capabilities.Act as the ultimate escalation point for complex technical decisions.Lead adoption of AI-assisted software engineering practices.Establish standards for prompt engineering, agent-based development, AI testing, AI observability, and AI governance.Drive AI integration throughout the software development lifecycle.Champion Domain-Driven Design (DDD), Behaviour-Driven Development (BDD), and Test-Driven Development (TDD).Define best practices for automated code generation, review, validation, and deployment.Establish engineering metrics and quality gates.AI Governance & RiskEnsure responsible AI implementation.Define controls around security, privacy, bias, explainability, and compliance.Collaborate with architecture, security, legal, and governance teams.Organizational ImpactMentor senior engineers and technical leads.Drive engineering capability development and innovation.Represent the organization in executive technical discussions.#J-*****-Ljbffr

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, AI, or equivalent experience. 12+ years of software engineering experience. 5+ years leading architecture or platform engineering initiatives. Deep expertise in cloud-native architecture and distributed systems. Strong understanding of modern AI/ML technologies, LLMs, agent frameworks, RAG, vector databases, and MLOps. Technical Expertise LLM orchestration RAG and knowledge systems CI/CD and DevSecOps AI governance frameworks Microservices and event-driven architectures Kubernetes and cloud platforms (Azure/AWS/GCP) Strategic technical leadership Executive communication Systems thinking Mentorship and coaching

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