FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
AI Engineer
EisnerAmper. Deploy and monitor AI models across Azure services with telemetry for performance, drift, and availability .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in deploying and managing AI models within Azure services, ensuring performance optimization and compliance through effective MLOps practices. Proficient in integrating various Azure tools and technologies to support scalable AI solutions across multiple applications.
Highest-signal resume keywords
MLOps ExperienceAzure Cloud EnvironmentAzure MLPerformance Testing ToolsChange Management Compliance
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Model DeploymentPerformance OptimizationVersion ControlInference Infrastructure TuningModel EvaluationFine-TuningInstruction TuningDomain AdaptationTelemetryIncident Response
Soft Skills
CollaborationConsulting BackgroundBias for Action
Tools & Technologies
Azure SynapseAzure Data LakeAzure App ServicesCosmos DBAzure AI FoundryAzure DevOpsApp InsightsLog AnalyticsKey VaultManaged Identity
Certifications & Qualifications
Bachelor's Degree in Computer ScienceBachelor's Degree in EngineeringBachelor's Degree in Data Science
Industry Keywords
AI SolutionsAuditAdvisoryClient-Facing ApplicationsGovernance Controls
Tech Stack
Tools & technologiesAzureCloudVault
About the role
Key responsibilities & impact- Deploy and monitor AI models across Azure services with telemetry for performance, drift, and availability
- Manage model upgrades, including APIs and UIs, with structured rollout, version control, and rollback support
- Optimize performance and cost through testing, profiling, and tuning of inference infrastructure and pipelines
- Implement MLOps pipelines for continuous integration, deployment, and lifecycle management using Azure ML and GitHub Actions
- Ensure compliant change management for AI-related deployments, including auditability, security, and governance controls
- Collaborate with AI Developers, Product Owners, Governance leaders, and Cloud Architects
- Support reliable, scalable, and cost-effective AI solutions across tax, audit, advisory, and client-facing applications
Requirements
What you’ll need- 5-7+ years in MLOps and/or AIOps
- Hands-on experience with Azure cloud environment
- Experience with Azure ML, Synapse, Data Lake, App Services, Cosmos DB, and Azure AI Foundry
- Bachelor's degree in Computer Science, Engineering, Data Science, or related technical field preferred
- Consulting background with a strong bias for action
- Knowledge of Prompt Flow, automation pipelines, and human-in-the-loop systems
- Experience with fine-tuning, instruction tuning, RLHF, and domain adaptation
- Experience integrating Azure DevOps, App Insights, Log Analytics, Key Vault, and Managed Identity
- Experience with inference performance testing and profiling tools such as Locust, K6, or custom scripts
- Knowledge of model evaluation, performance metrics, benchmark development, and A/B testing frameworks
- Understanding of model observability, telemetry, and incident response for AI systems
- Applicants must not require U.S. employment-based visa sponsorship; no sponsorship is available for H-1B, TN, O-1, E-3, H-1B1, J-1, or other employment-based visas
Benefits
Comp & perks- Flexibility to manage your days in support of work/life balance
- Culture recognized with multiple top “Places to Work” awards
- Merit-based employment
- Equal opportunity and nondiscrimination protections
- Application accommodations available upon request