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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and operating secure, scalable AI/ML platforms, with a strong focus on MLOps workflows, containerized applications, and CI/CD practices. Proficient in data pipeline orchestration, observability solutions, and infrastructure automation within distributed environments.
Highest-signal resume keywords
MLOps WorkflowsContainerized Application DeploymentCI/CD Pipeline DesignData Pipeline OrchestrationDevSecOps Principles
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Python ProgrammingKubernetesDockerCI/CDData Pipeline OrchestrationObservability SolutionsInfrastructure AutomationLinux EnvironmentsMachine Learning InfrastructureGenerative AI
Soft Skills
CollaborationTechnical LeadershipMentoring
Tools & Technologies
HelmGitOpsBuildahPodmanAWS
Industry Keywords
AI/MLMLOpsDevSecOpsCybersecurityHigh-Assurance Environments
Tech Stack
Tools & technologiesAWSCyber SecurityDistributed SystemsDockerKubernetesLinuxNoSQLPython
About the role
Key responsibilities & impact- Design, build, deploy, and operate secure, scalable AI/ML platform capabilities for Boeing BDS users and programs
- Develop and maintain data pipelines, workflow orchestration solutions, and data integration services
- Build and support MLOps workflows for training, experiment tracking, model registry, deployment, inference, monitoring, and lifecycle management
- Engineer and operate infrastructure for traditional machine learning and generative AI workloads, including on-premises and hybrid model serving
- Deploy, administer, and optimize containerized applications and platform services using Kubernetes
- Create and maintain Helm charts, deployment templates, automation scripts, and reusable platform patterns
- Implement CI/CD and GitOps workflows for secure, repeatable, observable software and model delivery
- Configure observability capabilities including metrics, logs, traces, dashboards, alerting, and reliability reporting
- Apply DevSecOps principles, including certificate management, secrets handling, access control, least privilege, and defense-in-depth controls
- Support data storage technologies including relational, NoSQL, search, graph, object, and vector platforms
- Build and maintain secure container images and software supply chain controls
- Collaborate with data scientists and application teams to productionize models and improve runtime performance
- Troubleshoot platform, data, networking, deployment, and performance issues across distributed environments
- Develop infrastructure-as-code and automation solutions
- Contribute to architecture decisions, standards, documentation, runbooks, and engineering best practices
- Support incident response, root cause analysis, reliability improvement, and continuous service optimization
- Partner with data scientists, software engineers, data engineers, cybersecurity teams, infrastructure teams, and business stakeholders
- Depending on level, provide technical leadership, influence architecture decisions, and mentor other data scientists
Requirements
What you’ll need- Bachelor’s degree or higher in computer science, computer engineering, software engineering, data engineering, information technology, mathematics, or a related technical field
- 3+ years of experience in software engineering, platform engineering, DevOps, site reliability engineering, data engineering, MLOps, machine learning infrastructure, or a related technical discipline
- 3+ years of experience developing software and automation solutions using Python
- 3+ years of experience building, deploying, operating, and orchestrating containerized applications using Docker, Podman, Buildah, and Kubernetes
- 3+ years of experience designing or supporting CI/CD pipelines and modern software delivery practices
- 3+ years of experience with data pipeline orchestration tools, production data workflows, databases, or production data platforms
- 3+ years of experience implementing monitoring, logging, alerting, or observability solutions for production systems
- 3+ years of experience working in Linux-based environments and troubleshooting distributed systems
- U.S. Person status required under 22 C.F.R. §120.62
- Must satisfy the Company’s Conflict of Interest assessment process
- Employer will not sponsor applicants for employment visa status
- Must live in the immediate area or relocate at own expense
- Subject to post-offer drug and alcohol testing when criteria are met
- Preferred: Master’s degree in a related technical field
- Preferred experience with cybersecurity, AI/ML and MLOps platforms, data engineering, Kubernetes, Helm, GitOps, CI/CD, observability, infrastructure automation, secure containerization, DevSecOps, generative AI, AWS, and high-assurance environments
Benefits
Comp & perks- Health insurance
- Flexible spending accounts
- Health savings accounts
- Retirement savings plans
- Life and disability insurance programs
- Paid and unpaid time away from work
- Up to 10% travel
- Relocation assistance is not provided; candidates must relocate at their own expense