Platform Engineer

At Schwab, you’re empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us “challenge the status quo” and transform the finance industry together.

We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s).

The Schwab Technology Services (STS) Research & Development team explores emerging technologies and turns them into practical capabilities that create measurable value across Schwab. We operate at the intersection of innovation and execution, rapidly testing ideas, partnering across the enterprise, and scaling what works.

The Infrastructure & Innovation Lab Engineer provides hands-on infrastructure engineering and operational support for an R&D incubation team focused on Generative AI, digital assets, and other emerging technologies. This role supports experimentation, demonstrations, and production-bound initiatives across GPU-enabled compute, cloud platforms, vendor solutions, automation, and specialized proof-of-concept environments.

The engineer applies established enterprise patterns and guardrails, partners with platform owners when an incubation need is not yet covered, and converts validated approaches into documented, repeatable patterns that can be reviewed, adopted, and supported by the appropriate enterprise teams.

• →Support digital asset infrastructure: Configure and support custody, wallets, tokenization, blockchain connectivity, signing, nodes, and vendor platforms.
• →Partner with security, risk, legal, architecture, and engineering teams on controls, integration needs, dependencies, and enterprise adoption.
• →Enable GenAI experimentation: Support model access, prompt and workflow tooling, RAG, agent orchestration, evaluation, safety testing, and observability.
• →Operate innovation lab environments: Maintain GPU workstations, GPU-enabled servers, operating systems, drivers, runtimes, firmware, patching, monitoring, and troubleshooting.
• →Create repeatable configurations for experiments and demonstrations.
• →Partner on cloud and platform needs: Use approved cloud patterns, reference architectures, controls, and services for incubation environments.
• →Apply Infrastructure-as-Code, CI/CD, GitOps, containers, and automation to improve repeatability and supportability.
• →Collaborate with cloud engineering and architecture on new or extended patterns, documentation, review, and handoff.
• →Manage technology vendors: Administer vendor environments, coordinate vendor relationships for lab, GenAI, digital assets, and emerging technology products.
• →Support secure paths to adoption: Embed security, risk, data, and operational requirements early in lab and incubation work.
• →Build proofs-of-concept and demonstrations that validate infrastructure approaches and production-readiness considerations.
• →Document configurations, dependencies, runbooks, decisions, and transition requirements.
• →Work with enterprise teams to transition successful experiments to production owners.

• 8+ years of experience in infrastructure, systems, platform, cloud, DevOps, site reliability, or a related engineering role.
• Working knowledge of Google Cloud Platform (GCP) and experience applying established enterprise cloud patterns.
• Strong experience with automation, scripting, Infrastructure-as-Code, source control, and CI/CD practices.
• Experience evaluating and managing technology vendors, including technical assessments, contracts, licensing, service coordination, and ongoing performance.
• Hands-on experience administering Linux systems, GPU compute environments, containers, and developer tooling.
• Ability to diagnose issues across hardware, operating systems, drivers, containers, cloud services, vendor platforms, and application dependencies.
• Clear written and verbal communication skills, including technical documentation and cross-functional collaboration.

• Experience with digital asset infrastructure or vendor platforms, such as custody, wallets, blockchain connectivity, signing, or node services.
• Experience with additional cloud providers, such as AWS or Azure.
• Experience configuring and operating EVM-based blockchain nodes, such as Ethereum, Besu, or ZKsync.
• Experience supporting GenAI or machine learning tools, model development environments, agentic harnesses, evaluation frameworks, or AI observability solutions.
• Familiarity with GPU drivers and runtimes.
• Familiarity with Terraform, Kubernetes, Docker, secrets management, and policy-as-code.
• Experience in a regulated or security-conscious enterprise environment.
• Experience working in research, incubation, or another emerging technology setting.

In addition to the salary range, this role is also eligible for bonus or incentive opportunities.