Senior Solutions Architect - Emerging Technologies (AI, GenAI, ML)

Jobtailor; Deutschland; Vor Ort; EUR 90.000 - 130.000; Vollzeit

Zusammenfassung

Jobtailor is seeking a senior AI/ML architect to lead discovery, design cloud-native, distributed systems, and AI-enabled solutions. You will craft target-state architectures, data flows, and integration patterns with a focus on scalable inference and security-by-design.

You will collaborate with business and technology partners to create roadmaps, migration designs, and reference architectures for AI platforms, while ensuring governance, privacy, and compliance across initiatives.

Qualifikationen

• Bachelor’s degree in CS/IS/Engineering or equivalent.
• 5+ years in agile software delivery with architecture responsibility.
• Experience designing distributed systems with microservices or serverless.
• Experience integrating AI/ML into applications and model serving.
• Experience with Java, Python, Node.js, or Scala.
• Experience with SQL and NoSQL data stores.
• Experience with at least one major cloud provider and core cloud patterns.
• Knowledge of CI/CD and DevOps practices.
• Strong communication translating business needs into technical direction.

Aufgaben

• Lead discovery with business and technology partners to understand objectives, constraints, current-state systems, and integration points.
• Document current-state architecture and define target-state designs including context diagrams, component designs, integration patterns, and data flows.
• Design and modernize applications into cloud-native architectures using microservices, serverless, and event-driven patterns.
• Create strategies, roadmaps, and migration designs for transitioning applications and data workloads to cloud platforms.
• Design AI and ML-enabled solutions, including model integration and scalable inference patterns.
• Design generative AI solution patterns, such as retrieval-augmented generation and prompt management.
• Define reference architectures for AI platforms, data pipelines, vector storage, and model endpoints.
• Establish MLOps and AI operation practices, including monitoring, drift detection, and cost management.
• Incorporate security-by-design practices including identity, encryption, and audit logging.
• Collaborate with governance to ensure privacy, explainability, and compliance.

Kenntnisse

Agile architecture

Distributed systems

AI/ML integration

Programming languages

Cloud platforms

CI/CD

DevOps practices

Communication

Ausbildung

Bachelor's degree in CS/IS/Engineering

Tools

AWS

Azure

GCP

Jobbeschreibung

Responsibilities

• Lead discovery with business and technology partners to understand objectives, constraints, current-state systems, and integration points.
• Document current-state architecture and define target-state designs including system context diagrams, component designs, integration patterns, and data flows.
• Design and modernize applications into cloud-compatible or cloud-native architectures using microservices, serverless, and event-driven patterns where appropriate.
• Create strategies, roadmaps, and migration designs for transitioning applications and data workloads to cloud platforms.
• Design AI and ML-enabled solutions, including model integration into products and business processes, and patterns for scalable inference and low-latency serving where needed.
• Design Generative AI solution patterns, such as retrieval-augmented generation, tool and API integration, prompt and context management, and evaluation approaches.
• Define reference architectures for AI platforms and enabling capabilities, such as data pipelines, feature and embedding generation, vector storage, model endpoints, and integration with enterprise APIs.
• Establish best practices for MLOps and AI operations, including model versioning, deployment, monitoring, drift detection, incident response, and cost management.
• Incorporate security-by-design practices into architectures, including identity and access controls, encryption, secrets management, secure networking, and audit logging.
• Partner with governance and risk stakeholders to ensure responsible AI considerations are incorporated, including privacy, explainability, safety, compliance, and model risk controls as applicable.
• Drive alignment and adoption of proposed solutions by clearly communicating tradeoffs, risks, and value and obtaining stakeholder alignment and governance approvals.
• Support teams responsible for testing and validation and help triage and resolve design-related issues found during development, UAT, or production.
• Perform other duties as assigned.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, Business, or equivalent practical experience.
• 5+ years of experience in agile software delivery environments with increasing architecture and design responsibility.
• Demonstrated experience designing distributed systems using microservices and or serverless patterns.
• Experience designing and integrating AI and ML capabilities into applications, including model serving considerations and data dependencies.
• Experience with one or more languages such as Java, Python, Node.js, or Scala.
• Experience with data persistence technologies across SQL and NoSQL.
• Experience with at least one major cloud provider, AWS, Azure, or Google Cloud, and core cloud design patterns.
• Working knowledge of CI/CD pipelines and DevOps practices, including automated testing and deployment automation.
• Strong communication skills and ability to translate business needs into clear technical direction.