AI Architect

This is a fully remote position, open to applicants in Portugal.

📋 Description

• Become a part of HBK’s Chief Digital Officer organization as our AI Architect, directly reporting to the Director of Digital Futures.

• Formulate and implement our enterprise AI strategy across various data ecosystems and platforms, including SAP, Salesforce, Microsoft 365 Co-Pilot, and internal team systems.

• Recognize high-value AI use cases, design intelligent agents, and assist teams in adoption and scaling processes.

• Contribute to defining our cutting-edge AI capabilities in serving our customers and colleagues.

• Develop strategies to enhance our architecture, aligning it with and supporting our business goals.

• Offer unique, industry-based technical thought leadership to our global digital, IT, and application teams.

• Shape the future of HBK's digital environment, promoting collaboration among international teams and establishing industry benchmarks.

• Create and execute enterprise-wide AI architectures for products and solutions, integrating automation, data governance, and secure-by-design principles within the organization.

• Lead the formulation and evaluation of AI system capability strategies and features that meet the business's strategic needs, ensuring the endorsement of all key stakeholders.

• Capture and prioritize market and environmental trends in AI that influence business strategies and objectives.

• Determine the business advantages of alternative strategies and develop persuasive business cases for the approval, funding, and prioritization of significant AI initiatives.

• Establish strategies, policies, standards, and practices to ensure alignment and compliance between business strategies, technology strategies, and enterprise transformation initiatives driven by AI.

• Create organizational policies, standards, and guidelines for AI solution configuration, design, deployment, and maintenance.

• Oversee the development of AI architectures for complex solutions, ensuring consistency with agreed-upon requirements.

• Set policies, principles, and practices for the selection of AI solution architecture components across HBK.

• Manage trade-offs while balancing functional, service quality, and systems management requirements for HBK.

• Maintain a stable and viable architecture at the enterprise level, ensuring design consistency and adherence to appropriate standards across the enterprise portfolio.

⛳️ Requirements

• AI Strategy & Innovation: Develop the enterprise AI strategy, identify and prioritize business use cases, assess emerging technologies, and create AI roadmaps that connect enterprise systems to intelligent workflows.

• Enterprise AI Architecture: Design AI systems, agent frameworks, RAG pipelines, and integration patterns while ensuring adherence to security, governance, and responsible AI standards.

• AI Solution Design & Implementation: Lead the design and development of AI agents and copilots that integrate with SAP, Salesforce, Microsoft 365, and other platforms. Provide training and support to teams adopting AI.

• Digital Transformation & AI Leadership: Advocate for adoption, coach cross-functional teams, and influence senior stakeholders regarding AI strategy and investment.

• Performance Measurement: Define OKRs and KPIs for AI initiatives and continuously assess solution performance.

• Autonomy: Operate under general direction and manage complex AI solution delivery to meet time, cost, and quality targets.

• Influence & Leadership: Influence stakeholders, build expert networks, and communicate complex AI concepts to non-technical audiences.

• Complexity Management: Navigate diverse enterprise systems and resolve technical and organizational barriers to AI adoption.

• Technical Expertise: Familiarity with Azure AI/OpenAI services, MLOps tooling, data governance, API integrations, cloud infrastructure, and secure AI engineering practices, including agentic/spec-driven development and orchestration.

• Knowledge: Understanding of machine learning and deep learning concepts, MLOps, model deployment, monitoring, and lifecycle management; data engineering and pipeline architecture (ETL/ELT, distributed systems); AI systems & platform knowledge; AI model integration with business applications; multi-agent architectures and orchestration frameworks; generative AI model usage and constraints; familiarity with AI platforms (Azure AI, AWS, Google Cloud, etc.); enterprise architecture & systems design skills across data, application, platform, and integration layers; scalable and secure architectures; AI-enhanced enterprise architecture patterns; digital twins for architecture scenario testing; knowledge graphs for grounding AI outputs; responsible AI, governance & security competence in responsible AI practices & compliance, data governance, access control, and lineage; guardrails for model safety and reliability; and vulnerability detection (e.g., prompt manipulation, model security).

• Experience: Designing large-scale distributed systems and integrating AI into enterprise workflows, deploying AI/ML systems, and integrating AI with enterprise platforms like SAP, Salesforce, and Microsoft 365, modernizing legacy platforms using AI-first strategies, and having cross-domain architecture experience (EA frameworks, cloud architecture, microservices, APIs) is an advantage.

🏝️ Benefits

• Competitive compensation and recognition for impactful contributions.

• Work From Anywhere policy supporting work-life balance.

• Comprehensive health insurance and generous vacation benefits.

• A culture of innovation, continuous learning, and global collaboration.

• Opportunities to work with international teams and access to learning resources for career advancement.