Architect - AI platforms Implementation and Integration
About The Position
This job is responsible for defining an architectural vision and solution aligned to the enterprise architecture strategy, technology, and platform choices. Key responsibilities include 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. Job expectations include 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. We are seeking a Architect with strong hands-on experience implementing and integrating AI platforms in alignment with approved enterprise architectures and AI control standards. This role focuses on execution and delivery, translating architectural designs and control requirements defined by Senior Architects into deployed, reliable solutions. The position emphasizes 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.
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
Nice To Haves
- Experience deploying AI or data platforms in on‑prem OpenShift environments, with focus on LangSmith or Galileo AI
- Familiarity with vector databases, RAG architectures, and LLM orchestration frameworks.
- Exposure to MLOps or LLMOps tools and workflows.
- Experience working in large-scale or regulated enterprise environments.
Responsibilities
- Consults with the business and operations to identify and understand challenges and opportunities to improve the use and effectiveness of technology, find creative solutions through knowledge of the domain, practical experiments, and Proof of Concepts, and aligns the solution intent and architectural vision to an evolving backlog of technology change
- Works with product management and other stakeholders to plan and prioritize technology focused backlog items for the architecture runway to enable business epics/features
- Performs design and code reviews to ensure all non-functional requirements for a solution are sufficiently met (for example, security, performance, maintainability, scalability, usability, and reliability)
- Leads rapid shaping of a high level architecture with details filled in with emerging business requirements and ensures architecture is flexible, modular, and designed to adapt easily
- Educates team members on the technology practices, standardization strategies, and best practices to create innovative solutions
- Clarifies the architecture and assists with system design for the development teams to support implementation and provides solution options to resolve any architectural impediments
- Utilizes the defined best practices, templates, and documentation to create architectural designs and suggests improvements to best practices and templates
- Implement and refine AI and data architecture solutions
- Deploy, configure, and operate vendor AI platforms and services within on‑prem OpenShift clusters.
- Support implementation of Generative AI solutions including LLM services, RAG pipelines, agents, and supporting data services.
- Apply standardized architectural patterns for scalability, reliability, and security.
- Implement predefined AI control standards related to security, privacy, access management, logging, and monitoring.
- Embed established & new Responsible AI mechanisms such as content filtering, prompt controls, telemetry, and explainability tooling.
- Ensure deployed solutions align with enterprise requirements for auditability, lineage, and approved usage patterns.
- Build, configure, and test integrations between AI platforms and enterprise systems including data platforms, identity services, monitoring tools, and other AI capabilities.
- Develop and maintain APIs, data pipelines, and event-driven integrations to support end‑to‑end AI solutions.
- Document technical implementations, deployment configurations, and operational dependencies.
- Support production readiness activities including validation, performance testing, observability configuration, and operational handoff.
- Troubleshoot deployment, runtime, and integration issues across AI platform components.
- Provide implementation feedback and identify technical gaps or improvement opportunities to Senior Architects.
Benefits
- access to paid time off
- resources and support to our employees
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
