- Defining an architectural vision and solution aligned to the enterprise architecture strategy, technology, and platform choices.
- Describing the solution intent/associated operating environment, evaluating system impacts, determining the primary systems/sub-systems and their interfaces, and assisting with end-to-end solution design.
- Defining non-functional requirements/architectural runway to support new epics/features and ensuring solutions are fit for purpose by working with stakeholders and service providers.
- Deploying vendor AI platforms in an on‑prem OpenShift environment, integrating AI capabilities across the enterprise ecosystem, and applying Responsible AI and governance standards without owning policy or assessment responsibilities.
- Consulting with the business and operations to identify and understand challenges and opportunities to improve the use and effectiveness of technology,
- Performing design and code reviews to ensure all non-functional requirements for a solution are sufficiently met.
- Leading rapid shaping of a high level architecture with details filled in with emerging business requirements and ensure architecture is flexible, modular, and designed to adapt easily.
- Educating team members on the technology practices, standardization strategies, and best practices to create innovative solutions.
- Clarifying the architecture and assisting with system design for the development teams to support implementation and providing solution options to resolve any architectural impediments.
Requirements
- 4–7 years of experience in data engineering, AI/ML platforms, platform engineering, or architecture‑adjacent roles.
- Hands‑on experience deploying and operating applications on Kubernetes or OpenShift platforms.
- Experience implementing system integrations using APIs, data pipelines, and event‑based architectures.
- Working knowledge of AI/ML and Generative AI platforms, components, and deployment patterns.
- Proficiency in Python and SQL; familiarity with containerized workloads.
- Understanding of enterprise security, identity, logging, and operational requirements.
- Strong execution, problem‑solving, and collaboration skills.
- Hands‑on AI platform implementation and integration Kubernetes / OpenShift deployment expertise.
- Application of architectural standards and AI controls.
Core Competencies
Demonstrates expertise in defining architectural solutions aligned with enterprise strategies, deploying AI platforms in OpenShift environments, and implementing system integrations using APIs and data pipelines. Proficient in Python and SQL, with a strong focus on collaboration and problem‑solving to enhance technology effectiveness.
Highest-signal resume keywords
- AI/ML Platform Implementation
- Kubernetes/OpenShift Deployment
- System Integration Using APIs
- Python Proficiency
- Data Engineering Experience
ATS Optimization Keywords
Hard Skills
- AI/ML Platforms
- Platform Engineering
- System Integrations
- Data Pipelines
- Event-Based Architectures
- Python
- SQL
- Containerized Workloads
- Architectural Standards
- AI Controls
Soft Skills
- Execution
- Problem‑Solving
- Collaboration
Industry Keywords
- Enterprise Architecture
- Non-Functional Requirements
- Responsible AI
- Governance Standards
- Operational Requirements
Tools & Technologies
- OpenShift
- Kubernetes