Health Catalyst

2 weeks ago

Site Reliability Engineer- AI Enablement

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 16 hours agoStatus: Live

Job Summary

Help the Central AI team enable engineering orgs to adopt AI responsibly and effectively. You’ll coach teams on AI workflows (AI-assisted coding, prompt practices, agentic patterns), review AI architectures for reliability and observability, and advise on SLOs, failure modes, and operational readiness for AI-powered services. Partner with product, data science, security, and compliance to translate AI governance into practical, reusable standards and documentation.

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Seniority: Mid level

Key Responsibilities

•Train and coach engineering teams to integrate AI into development workflows, including AI-assisted coding, prompt engineering, and agentic development patterns.
•Evaluate AI system designs through the Central AI intake process, providing guidance on integration patterns, reliability risks, observability gaps, and AI governance alignment.
•Provide technical guidance for the AI governance framework, including model access, data handling, risk tiers, and responsible AI use.
•Support AI solutioning and implementation by advising teams on LLM integration, RAG pipelines, agentic architectures, and AI service patterns.
•Advise on reliability for AI-powered services using an SRE perspective: observability, SLOs, failure modes, operational readiness, and AI-specific guidance during incidents.

Key Requirements

•5+ years of experience in site reliability engineering, platform engineering, or a closely related role.
•2+ years of hands-on experience solutioning or implementing AI/LLM-based systems in production or near-production contexts.
•Hands-on experience with at least one agentic or RAG framework (e.g., LangChain, LlamaIndex, Semantic Kernel).
•Strong SRE or platform engineering background with observability, reliability principles, and operational best practices.
•Experience advising or enabling engineering teams through coaching, reviews, or training on AI tooling and best practices.

Experience:5+ yearsHealthcare ITAILLMs

Education:Master's in Computer Science, Information Systems, or related technical field

Skills:CommunicationCross-functional collaborationCoachingSelf-directedProblem-solving

Tech Stack:Azure AI FoundryAnthropic ClaudeLangChainLlamaIndexSemantic KernelLLM APIRAG pipelinesAgentic architecturesAzureAWSDockerKubernetesCI/CDDatadogGrafanaOpenTelemetryDatabricksHL7v2CDAEMR

Company Brief

Health Catalyst

Provides a data and analytics platform and services that help healthcare organizations improve clinical, financial, and operational outcomes by aggregating and analyzing healthcare data to support decision-making, performance improvement, and value-based care initiatives.

Industry: HealthTech

Company Size: Enterprise (1,001+ employees)

Revenue: USD 250M to 500M

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Salt Lake City, United States

Founded: 2008

Website LinkedIn

Loading job details...

Preparing the role view and application actions.

Health Catalyst

2 weeks ago

Site Reliability Engineer- AI Enablement

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 16 hours agoStatus: Live

Job Summary

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Seniority: Mid level

Key Responsibilities

•Train and coach engineering teams to integrate AI into development workflows, including AI-assisted coding, prompt engineering, and agentic development patterns.
•Evaluate AI system designs through the Central AI intake process, providing guidance on integration patterns, reliability risks, observability gaps, and AI governance alignment.
•Provide technical guidance for the AI governance framework, including model access, data handling, risk tiers, and responsible AI use.
•Support AI solutioning and implementation by advising teams on LLM integration, RAG pipelines, agentic architectures, and AI service patterns.
•Advise on reliability for AI-powered services using an SRE perspective: observability, SLOs, failure modes, operational readiness, and AI-specific guidance during incidents.

Key Requirements

•5+ years of experience in site reliability engineering, platform engineering, or a closely related role.
•2+ years of hands-on experience solutioning or implementing AI/LLM-based systems in production or near-production contexts.
•Hands-on experience with at least one agentic or RAG framework (e.g., LangChain, LlamaIndex, Semantic Kernel).
•Strong SRE or platform engineering background with observability, reliability principles, and operational best practices.
•Experience advising or enabling engineering teams through coaching, reviews, or training on AI tooling and best practices.

Experience:5+ yearsHealthcare ITAILLMs

Education:Master's in Computer Science, Information Systems, or related technical field

Skills:CommunicationCross-functional collaborationCoachingSelf-directedProblem-solving

Tech Stack:Azure AI FoundryAnthropic ClaudeLangChainLlamaIndexSemantic KernelLLM APIRAG pipelinesAgentic architecturesAzureAWSDockerKubernetesCI/CDDatadogGrafanaOpenTelemetryDatabricksHL7v2CDAEMR

Company Brief

Health Catalyst

Industry: HealthTech

Company Size: Enterprise (1,001+ employees)

Revenue: USD 250M to 500M

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Salt Lake City, United States

Founded: 2008

Website LinkedIn