Your opportunity

At Charles Schwab, our purpose is simple: we champion client’s goals with passion and integrity. Guided by honesty, mutual respect and a commitment to doing what’s right, we bring innovation, education, and service together to help shape financial futures. Our people are the foundation of our success – they approach their work with curiosity and collaboration, coming together to create solutions that make a meaningful impact for clients and communities. As we expand into India, we are bringing this same culture of inclusion, learning, and opportunity to new talent. Joining us means becoming part of a global team where your work matters and your future can take shape.

Our Hyderabad location is central to Schwab’s growth, bringing together talented people and technology to drive innovation, scale and efficiency. Here, you will work alongside teams who create solutions that support millions of clients every day. The work you do is more than daily operations – it’s a chance to experiment, learn, and build within a values-driven, supportive environment. This is a unique opportunity to be part of our early growth phase and shape something new, backed by the stability and strength of a Fortune 500 company. Your impact begins on day one, and your contributions will help define our future in the region

We are seeking an AI Site Reliability Engineer to join a forward-thinking engineering team that builds intelligent observability, monitoring, deployment automation, and production support solutions using AI-augmented development practices. This role includes hands-on production support for Pega Infinity applications, where you will apply engineering rigor to improve platform stability, accelerate incident response, and strengthen operational resilience. You will build software solutions for operational challenges, leveraging Gen AI to automate triage, streamline root cause analysis, and drive systems toward five 9s (99.999%) availability while ensuring capacity planning, redundancy, and the highest standards of reliability, security, and scalability. This is a hands-on engineering role where you will actively contribute to architecture, code, AI-driven tooling, and the continuous improvement of Pega production operations. Ideal for engineers who are curious, adaptable, and excited about working at the intersection of software engineering, AI, and mission-critical platform support.

Key Responsibilities:

High Availability & Resilience

Design and implement architectures that achieve and sustain 99.999% uptime across critical systems and Pega Infinity application environments

Define, measure, and track SLOs, SLIs, and error budgets

Build AI-powered self-healing systems with automated failover, redundancy, and graceful degradation

Perform AI-assisted capacity planning, demand forecasting, and load testing

Conduct chaos engineering practices enhanced with AI-driven failure prediction

Production Support for Pega Infinity Applications

Provide engineering-led production support for Pega Infinity applications, ensuring platform stability, incident resolution, and operational continuity

Monitor application health, queues, integrations, and batch processes to proactively identify and resolve issues before business impact occurs

Lead incident triage, troubleshooting, and service restoration for Pega production issues, partnering across infrastructure, middleware, database, and development teams as needed

Use Gen AI to accelerate incident investigation, summarize signal patterns, and recommend next-best actions for recurring operational problems

Drive permanent fixes through post-incident analysis, defect prevention, runbook improvements, and automation of repetitive support tasks

Observability & Monitoring

Design, build, and maintain AI-enhanced observability platforms covering metrics, logs, traces, and intelligent alerting

Implement AI-powered anomaly detection, predictive alerting, and proactive system health management for shared services and Pega application workloads

Leverage Gen AI to auto-generate and refine dashboards, alert rules, and runbooks

Build real-time availability dashboards with AI-driven trend analysis tracking 99.999% targets

Root Cause Analysis

Build AI-accelerated root cause analysis with thorough postmortems and actionable remediation

Build AI-powered diagnostic tools that automatically correlate logs, metrics, traces, and Pega operational signals

Use Gen AI to analyze incident patterns, predict recurring failures, and recommend preventive actions

Build AI agents that automate initial triage and preliminary RCA for common incident types

Continuously reduce MTTD and MTTR through AI-assisted workflows

Deployment Automation

Design and maintain AI-enhanced CI/CD pipelines with AI-driven deployment risk scoring

Implement progressive delivery with canary releases, blue-green deployments, and automated rollbacks triggered by AI anomaly detection

Leverage Gen AI to generate deployment scripts, IaC templates, and pipeline configurations

Support production releases, hotfixes, and change implementations for Pega Infinity applications with strong operational controls and risk awareness

Eliminate manual toil by building AI agents for repetitive operational tasks

AI-Driven Development

Use GenAI tools (GitHub Copilot, Cursor, ChatGPT) for coding, debugging, documentation, and operations

Developer ownership is non-negotiable. All code, whether human or AI-generated, must be reviewed, tested, and understood before merging

Design and develop AI agents for incident response, log analysis, capacity management, and operational automation

Define agent goals, tool use, memory, and orchestration logic for multi-step SRE workflows

Apply spec-driven development and continuously evaluate emerging Gen AI tools

Testing & Quality

Leverage Gen AI to generate tests, identify coverage gaps, and create edge-case scenarios

Drive AI-powered security scanning, performance testing, and reliability validation early in development

Modernization & Collaboration

Modernize existing monitoring, alerting, deployment, and support processes using AI-assisted workflows

Identify technical debt and propose AI-accelerated remediation strategies with measurable outcomes

Participate in architecture discussions, design reviews, code reviews, and production readiness activities

Develop and maintain prompt engineering guidelines and custom instructions for consistent AI-assisted development

Share learnings, patterns, and tooling insights with the broader team

What you have

Required Qualifications:

8+ years of software engineering experience with a strong focus on SRE, DevOps, platform engineering, or enterprise application production support

Bachelor's degree in Computer Science or equivalent

Hands-on technically with ability to architect, review code, and contribute to critical decisions

Proven experience operating systems at 99.99% or higher availability

Hands-on experience supporting and troubleshooting enterprise production applications, including incident triage, root cause analysis, and service restoration

Hands-on experience with Pega Infinity applications in production support, platform operations, or engineering roles

Strong hands-on knowledge of Pega operational constructs and troubleshooting, including queues, agents, node types, DDS, Kafka, integrations/APIs, and database troubleshooting

Hands-on experience with GenAI coding tools and demonstrated ability to apply them effectively

Proficiency in .NET, with scripting skills in Python, Bash, or PowerShell

Experience building AI agents for operational automation

Strong prompt engineering skills with ability to contribute to team-level AI practices

Deep understanding of HA patterns including active-active, multi-region failover, and distributed consensus

Hands-on experience with observability platforms (Datadog, Splunk, Grafana, or similar)

Strong experience with CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions or similar)

Proven track record leading RCA efforts and driving reliability improvements

Proven experience diagnosing production issues end-to-end, identifying root cause, and partnering with development teams on corrective and preventative improvements

Strong CS fundamentals including system design, networking, concurrency, and algorithms

Preferred Qualifications:

Experience with Oracle, Mongo, SQL DBs

Experience with cloud platforms (PCF, GCP, AWS, or Azure)

Experience with containerization and orchestration (Docker, Kubernetes)

Knowledge of chaos engineering and ML-powered anomaly detection

Experience with legacy system modernization

Pega Infinity platform knowledge, including application support, deployment, and troubleshooting concepts

Experience with Pega platform components and integrations, such as queues, agents, node classification/types, DDS, Kafka, and API-based integrations

Experience troubleshooting database performance, query issues, and data-related failures in enterprise application environments

Experience supporting workflow-driven enterprise applications in regulated or high-availability environments