1 day ago
Arlington, VA, USA or Seattle, WA, USASenior
Base Salary
$138k - $186k/yr
Responsibilities
- Design, build, deploy, and operate secure and scalable AI/ML platform capabilities.
- Develop data pipelines, workflow orchestration solutions, and data integration services for analytics and machine learning.
- Build and support MLOps workflows for training, experiment tracking, model registry, deployment, inference, monitoring, and lifecycle management.
- Engineer infrastructure for traditional machine learning and generative AI workloads across on-premises and hybrid environments.
- Deploy and administer containerized applications using Kubernetes and related ecosystem tools.
- Create Helm charts, deployment templates, automation scripts, and reusable platform patterns.
- Implement CI/CD and GitOps workflows for secure and observable software and model delivery.
- Configure observability capabilities including metrics, logs, traces, dashboards, alerting, and reliability reporting.
- Apply DevSecOps controls including certificate management, secrets handling, access control, least privilege, and defense in depth.
- Support relational, NoSQL, search, graph, object, vector, and analytical data platforms.
- Build secure container images and software supply-chain controls, including vulnerability scanning and artifact management.
- 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 to provision and manage platform resources.
- Contribute to architecture decisions, standards, documentation, runbooks, and engineering best practices.
- Support incident response, root-cause analysis, reliability improvement, and service optimization.
Requirements
- Bachelor’s degree or higher in computer science, computer engineering, software engineering, data engineering, information technology, mathematics, or a related technical field.
- At least 3 years of experience in software engineering, platform engineering, DevOps, site reliability engineering, data engineering, MLOps, machine learning infrastructure, or a related discipline.
- At least 3 years of experience developing software and automation with Python.
- At least 3 years of experience building, deploying, operating, and orchestrating containerized applications with Docker, Podman, Buildah, and Kubernetes.
- At least 3 years of experience designing or supporting CI/CD pipelines and modern software delivery practices.
- At least 3 years of experience with data pipeline orchestration, production data workflows, databases, or production data platforms.
- At least 3 years of experience implementing monitoring, logging, alerting, or observability for production systems.
- At least 3 years of experience working in Linux-based environments and troubleshooting distributed systems.
- Preferred qualifications include a master’s degree or experience with end-to-end AI/ML, data, and MLOps platforms.
- Preferred experience includes Kubernetes platform engineering, Helm, ArgoCD, GitLab, Prometheus, Grafana, Loki, Tempo, Mimir, OpenTelemetry, Terraform, OpenTofu, Pulumi, Ansible, shell scripting, and Python automation.
- Preferred experience includes secure containerization, SBOM generation, image signing, TLS, certificate management, secrets management, RBAC, least privilege, policy enforcement, model serving, model monitoring, LLM deployment, and retrieval-augmented generation.
- Knowledge of AWS data and machine learning services and experience in defense, aerospace, regulated, or other high-assurance environments is preferred.
- Candidates must satisfy Boeing’s conflict-of-interest assessment and U.S. export-control requirements.
Benefits
- Eligible employees may receive health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance, and paid and unpaid time away from work.
- Relocation assistance is not negotiable; candidates must live in the immediate area or relocate at their own expense.
- The position may require travel up to 10% of the time.
- This is a Shift 1 position in the United States of America.
- The position is not safety-sensitive and does not require a security clearance.
Categories
About Boeing
Boeing designs, manufactures, and services commercial airplanes along with defense and space systems for airlines, governments, and space agencies worldwide. It sells aircraft and related systems plus aftermarket support and lifecycle services. Founded in 1916 and headquartered in Arlington, VA, Boeing is a public company listed on the NYSE (BA), with notable programs including the 737/787 families and work on NASA space initiatives.