Sr.Specialist, AI Site Reliability Engineer - Core Enterprise Services

Your opportunity

At Charles Schwab, our purpose is simple: we championclients’goals with passion and integrity. Guided by honesty, mutualrespectand a commitment to doingwhat’sright, 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’sa chance to experiment, learn, and build within avalue–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, and deployment automation solutions using AI-augmented development practices. This is not traditional production support. You will build software solutions for operational challenges,leveragingGen AI to accelerate workflows, automate incident response, 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, and AI-driven tooling. Ideal for engineers who are curious, adaptable, and excited about working at the intersection of software engineering and AI.

KeyResponsibilities:

High Availability & Resilience

Design and implement architectures that achieve and sustain 99.999% uptime across critical systems
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
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
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, and traces
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
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, and deployment systems using AI-assisted workflows
Identify technical debt and propose AI-accelerated remediation strategies with measurable outcomes
Participate in architecture discussions, design reviews, and code reviews
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 support

• Bachelor's degree in Computer Engineering, Computer Science, Information Technology, or equivalent

• Hands-on technical ability to architect, review code, and contribute to critical engineering and operational decisions

• Proven experience operating systems at 99.99% or higher availability
  Hands-on experience with GenAI coding tools anddemonstratedability to apply them effectively

• Proficiencyin Java or .NET, with scripting skills in Python, Bash, or PowerShell

• Strong experience providing production support for enterprise applications, including incident triage, root cause analysis, and service restoration

• Hands-on experience with Pega Infinity applications, including troubleshooting case processing, data pages, connectors, services, background jobs, queues, agents, node types, and environment issues in production or pre-production environments

• Experience working with Pega diagnostic and support tooling, including tracer, clipboard, logs, alerts, performance analysis, and monitoring dashboards

• Experience supporting integrations such as REST, SOAP, messaging, and database interactions within Pega applications

• Experience supporting application releases, hotfixes, and patch deployments with strong change management discipline

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

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

• Proventrack recordleading RCA efforts and driving reliability improvements

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

• Strong understanding of Pega guardrails, performance tuning concepts, and operational considerations forhighly availableenterprise applications

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

PreferredQualifications:

• Experience with Mongo, Oracle, SQL

• 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