Tech Lead_Sr Manager, Software Development & Engineering

Charles Schwab Inc.•Austin, TX

8d•$150,600 - $200,000•Onsite

About The Position

Schwab Technology Services is building the technology that helps create more connected, reliable, and personalized experiences for millions of clients. In this role, you will help build and evolve the Schwab Customer Identifier platform, the unified identity layer that helps resolve the same client across Schwab affiliates and supports a more complete view of each customer across lines of business. As a Lead Software Engineer, you will provide hands-on technical leadership while remaining close to the code. You will use Java, Systems Engineering, REST APIs, Microservices, Cloud Services Management, DevOps, Data Management, Generative AI, and Stakeholder Management to design scalable solutions, guide architecture decisions, improve engineering quality, and help the team deliver client-facing functionality from scoping through production rollout. This is an opportunity to shape a critical platform, influence modern engineering practices, and contribute to technology that supports Schwab’s client-first mission.

Requirements

Demonstrated expertise in Java development, including designing, building, and supporting high-volume, highly available enterprise applications
Ability to provide Technical Leadership by setting direction, guiding architecture decisions, mentoring engineers, and raising engineering standards across delivery teams
Strong Systems Engineering capability, including designing scalable, resilient, maintainable systems across applications, services, and data flows
Experience designing and supporting REST APIs, Microservices, and enterprise integration patterns that enable reliable system interoperability
Experience with Cloud Services Management and cloud-based deployment practices in a CI/CD delivery model
Demonstrated DevOps mindset, including continuous build, source control, deployment automation, code quality, and production ownership
Strong Data Management experience with relational or NoSQL databases, data models, data integrity, and real-time or batch data movement
Ability to use Generative AI or AI-assisted engineering tools responsibly to support code development, testing, review, documentation, and automation while maintaining ownership of quality and correctness
Strong Stakeholder Management skills, including the ability to partner with product, architecture, vendors, offshore teams, and internal stakeholders to drive delivery outcomes

Nice To Haves

Experience working in product-engineering environments where engineers own systems, outcomes, and production quality
Experience with PostgreSQL, MongoDB, Yugabyte, event-driven systems, message queues, or streaming platforms
Experience with GCP, PCF, AWS, Azure, or similar cloud and platform environments
Experience translating low-level design elements, API contracts, class structures, and data models into structured specifications
Experience establishing team-level engineering practices for code quality, AI-assisted workflows, automation, test coverage, and delivery consistency
Ability to influence technical strategy, lead proof-of-concepts, evaluate new technologies, and guide decisions using data, risk, and business impact

Responsibilities

Provide hands-on technical leadership while remaining close to the code.
Use Java, Systems Engineering, REST APIs, Microservices, Cloud Services Management, DevOps, Data Management, Generative AI, and Stakeholder Management to design scalable solutions.
Guide architecture decisions.
Improve engineering quality.
Help the team deliver client-facing functionality from scoping through production rollout.
Shape a critical platform.
Influence modern engineering practices.
Contribute to technology that supports Schwab’s client-first mission.
Set direction, guide architecture decisions, mentor engineers, and raise engineering standards across delivery teams.
Design scalable, resilient, maintainable systems across applications, services, and data flows.
Design and support REST APIs, Microservices, and enterprise integration patterns that enable reliable system interoperability.
Manage cloud services and cloud-based deployment practices in a CI/CD delivery model.
Demonstrate a DevOps mindset, including continuous build, source control, deployment automation, code quality, and production ownership.
Manage data with relational or NoSQL databases, data models, data integrity, and real-time or batch data movement.
Use Generative AI or AI-assisted engineering tools responsibly to support code development, testing, review, documentation, and automation while maintaining ownership of quality and correctness.
Partner with product, architecture, vendors, offshore teams, and internal stakeholders to drive delivery outcomes.
Establish team-level engineering practices for code quality, AI-assisted workflows, automation, test coverage, and delivery consistency.
Influence technical strategy, lead proof-of-concepts, evaluate new technologies, and guide decisions using data, risk, and business impact.
Continue building depth in enterprise identity platforms, cloud-based engineering, distributed systems, AI-assisted development, and technical leadership.
Expand expertise in Generative AI, agentic workflows, spec-driven development, platform resiliency, cloud deployment, and enterprise-scale systems design.
Deepen ability to influence architecture, guide engineering standards, partner across teams, and mentor engineers in a complex, high-impact technology environment.