AI Platform Engineer

Job highlights Identified by Google from the original job post Qualifications • 15+ years of experience in software development with significant focus on AI architecture and system design • Proven experience designing distributed, scalable, and high-availability systems • Strong hands-on experience with Microsoft Azure • Proficiency in Python • Mandatory healthcare domain experience, preferably in the Payer domain • 1–2 years of hands-on GenAI experience, specifically on Azure, with production deployment exposure • Hands-on experience with CI/CD and infrastructure automation, including Azure Pipelines and Bicep • Terraform experience acceptable with readiness to transition to Bicep • Strong communication skills with the ability to explain technical concepts to non-technical stakeholders • 6 more items(s) Responsibilities • Define’s Client enterprise AI strategy and architecture, including platform selection, LLM evaluation, governance model, technical standards, and alignment with Client’s long-term digital and analytics roadmap • Lead the assessment and selection of AI platforms, LLMs, vector databases, orchestration layers, and supporting components, ensuring technology recommendations are vendor neutral and based on Client’s use cases, data landscape, regulatory requirements, and scalability needs • Identify, evaluate, and prioritize business processes, workflows, and functions suitable for AI enablement, providing clear guidance on where AI should and should not be applied based on business value, risk, feasibility, and compliance considerations • Design end-to-end solution architectures for approved AI initiatives, including integration patterns, data flows, model hosting, API interfaces, prompt frameworks, guardrails, and monitoring approaches • Provide hands-on development and technical implementation support on a case-by-case basis, which may include building prototypes, developing automation scripts, designing prompts, integrating APIs, or creating reference implementations • Collaborate with Client’s engineering, data, security, and product teams to ensure AI solutions align with enterprise architecture, data governance, privacy/security standards, and compliance requirements (including HIPAA) • Establish and document AI best practices, including coding patterns, evaluation frameworks, testing approaches, prompt design standards, and model performance monitoring guidelines • Support change management, training, and capability uplift initiatives, helping Client teams understand how to adopt, scale, and maintain AI solutions across the enterprise • Provide ongoing advisory to leadership, offering strategic insights, risk assessments, ROI analysis, and recommendations related to AI investments, vendor partners, operating models, and organizational structure • Participate in Agile ceremonies and cross-functional planning sessions to ensure AI work aligns with product roadmaps, release plans, and enterprise priorities • Deliver architectural documentation, solution diagrams, decision logs, and other artifacts required to support clarity, governance, and sustainable adoption across the organization • 8 more items(s) More job highlights Job description Purpose of the Role

• Define’s Client enterprise AI strategy and architecture, including platform selection, LLM evaluation, governance model, technical standards, and alignment with Client’s long-term digital and analytics roadmap.

• Lead the assessment and selection of AI platforms, LLMs, vector databases, orchestration layers, and supporting components, ensuring technology recommendations are ...vendor neutral and based on Client’s use cases, data landscape, regulatory requirements, and scalability needs.

Identify, evaluate, and prioritize business processes, workflows, and functions suitable for AI enablement, providing clear guidance on where AI should and should not be applied based on business value, risk, feasibility, and compliance considerations.

• Design end-to-end solution architectures for approved AI initiatives, including integration patterns, data flows, model hosting, API interfaces, prompt frameworks, guardrails, and monitoring approaches.

• Provide hands-on development and technical implementation support on a case-by-case basis, which may include building prototypes, developing automation scripts, designing prompts, integrating APIs, or creating reference implementations.

• Collaborate with Client’s engineering, data, security, and product teams to ensure AI solutions align with enterprise architecture, data governance, privacy/security standards, and compliance requirements (including HIPAA).

• Establish and document AI best practices, including coding patterns, evaluation frameworks, testing approaches, prompt design standards, and model performance monitoring guidelines.

• Support change management, training, and capability uplift initiatives, helping Client teams understand how to adopt, scale, and maintain AI solutions across the enterprise.

• Provide ongoing advisory to leadership, offering strategic insights, risk assessments, ROI analysis, and recommendations related to AI investments, vendor partners, operating models, and organizational structure.

• Participate in Agile ceremonies and cross-functional planning sessions to ensure AI work aligns with product roadmaps, release plans, and enterprise priorities.

• Deliver architectural documentation, solution diagrams, decision logs, and other artifacts required to support clarity, governance, and sustainable adoption across the organization.

Required Qualifications

• 15+ years of experience in software development with significant focus on AI architecture and system design

• Proven experience designing distributed, scalable, and high-availability systems

• Strong hands-on experience with Microsoft Azure

• Proficiency in Python

• Mandatory healthcare domain experience, preferably in the Payer domain

• 1–2 years of hands-on GenAI experience, specifically on Azure, with production deployment exposure

• Hands-on experience with CI/CD and infrastructure automation, including Azure Pipelines and Bicep

• Terraform experience acceptable with readiness to transition to Bicep

• Strong communication skills with the ability to explain technical concepts to non-technical stakeholders

Preferred / Nice-to-Have

• Azure certifications (e.g., Azure Solutions Architect Expert)

• Experience working with regulated environments (HIPAA compliance)

• Exposure to multi-cloud or hybrid cloud architectures

• Experience influencing architecture decisions at an enterprise level Show full description Report this listing Loading...