Software Engineer – AI/ML Platform Operations

AAA

. Lead operational excellence, reliability, and support for enterprise AI and data platforms .

Posted 10/28/2026full-timePhoenix • Arizona • United StatesMid-LevelSenior💰 $105,345 - $140,550 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in leading operational excellence and reliability for AI and data platforms, with a strong focus on MLOps practices, cloud-native technologies, and automation. Capable of providing technical leadership and mentoring while ensuring performance, security, and governance across AI workloads.

Highest-signal resume keywords

AI/ML Platform LeadershipCloud Operations in AWSMLOps Best PracticesCI/CD and Automation ToolsTechnical Communication Skills

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

PythonJavaJavaScriptTypeScriptNode.jsMLOpsObservabilityMonitoring SolutionsRoot Cause AnalysisOperational Tooling

Soft Skills

Technical LeadershipCollaborationCommunicationTroubleshootingMentoring

Tools & Technologies

Palantir FoundryAWS BedrockAmazon SageMakerJenkinsMavenGitHub ActionsDatadogSplunkGrafanaCloudWatch

Certifications & Qualifications

Cloud CertificationsAI/ML CertificationsDevOps CertificationsPlatform Engineering Certifications

Industry Keywords

Operational ExcellenceGenerative AIAI GovernanceModel Risk ManagementCloud-Native Services

Tech Stack

Tools & technologies

AWSCloudGrafanaJavaJavaScriptJenkinsMavenNode.jsPrometheusPythonSplunkTypeScript

About the role

Key responsibilities & impact

Lead operational excellence, reliability, and support for enterprise AI and data platforms
Provide technical leadership for AI/ML platforms including Palantir Foundry, AWS Bedrock, Amazon SageMaker, and related cloud-native technologies
Ensure reliability, scalability, performance, security, and operational readiness for production AI workloads
Support deployment, monitoring, maintenance, and lifecycle management of AI/ML solutions and Generative AI services
Establish operational standards, support models, service-level objectives, and platform governance practices
Design and implement automation, monitoring, observability, and operational tooling
Develop and maintain dashboards, health metrics, alerts, logging frameworks, and operational runbooks
Enhance CI/CD pipelines, deployment automation, infrastructure-as-code, and model release processes
Implement MLOps best practices, model monitoring, model lifecycle management, and AI operational governance
Serve as a senior escalation point for complex production issues involving AI platforms, machine learning workloads, cloud infrastructure, and data integrations
Lead root cause analysis and corrective/preventive actions
Resolve performance, availability, deployment, and integration issues across AI and data ecosystems
Partner with engineering and business teams to restore service and minimize operational risk
Mentor engineers and platform teams and provide technical guidance
Influence platform strategy, architecture decisions, operational processes, and technology adoption
Collaborate across Data Engineering, Data Science, Architecture, Infrastructure, Security, and Product teams
Communicate complex technical concepts to technical and non-technical audiences
Identify opportunities to improve operational efficiency, governance, security, and developer experience
Champion automation, observability, DevOps, SRE, and AIOps practices

Requirements

What you’ll need

6+ years of progressive experience in software engineering, platform engineering, cloud operations, MLOps, DevOps, or related technical disciplines
Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent practical experience
Experience supporting production cloud-based applications and services in AWS environments
Strong experience with software engineering and automation using Python, Java, JavaScript/TypeScript, or Node.js
Experience with CI/CD, build, integration, and deployment tools such as Jenkins, Maven, GitHub Actions, or equivalent
Experience with cloud-native services including compute, storage, networking, databases, and serverless architectures
Experience building and maintaining operational monitoring, observability, and alerting solutions
Strong troubleshooting, incident response, and root cause analysis skills
Excellent communication, collaboration, and technical leadership capabilities
Experience with AI/ML platforms such as Palantir Foundry, Amazon SageMaker, AWS Bedrock, Databricks, or similar ecosystems
Experience supporting Generative AI applications, LLM-based solutions, prompt orchestration frameworks, and Retrieval-Augmented Generation (RAG) architectures
Knowledge of MLOps practices including model deployment, monitoring, governance, experimentation, and lifecycle management
Experience with observability and monitoring platforms such as Datadog, Splunk, Grafana, Prometheus, CloudWatch, or OpenTelemetry
Familiarity with AI governance, responsible AI principles, model risk management, and operational controls
Relevant cloud, AI/ML, DevOps, or platform engineering certifications
Must have authorization to work indefinitely in the US
CSAA does not provide visa sponsorship for this role
Willingness to travel as needed for divisional/team meetings and other in-person meetings

Benefits

Comp & perks

Annual bonus eligibility / company-wide annual discretionary bonus through the Annual Incentive Plan (AIP), of up to 8% of eligible pay
401(k) with a company match
Career growth, leadership and mentorship support
Flexible Workplace and remote-first culture
Primarily work from home with flexibility to work from various locations including CSAA offices
Reasonable accommodations for qualified applicants and employees with disabilities or other limitations