AI-enabled Site Reliability Engineering

EY; Hyderabad, Pune District, Bengaluru; Híbrido; INR 3 500 000 - 5 500 000; Tempo integral

Resumo da oferta

EY Hyderabad is seeking an AI Site Reliability Engineer to join a forward‑looking team building AI‑augmented observability, deployment automation, and production support for Pega Infinity applications.

You will drive 99.999% availability, AI‑driven triage, and resilient platform operations while collaborating across infrastructure, middleware, and development teams.

Qualificações

• 8+ years of software engineering with SRE/DevOps focus.
• Bachelor's degree in Computer Science or equivalent.
• Hands-on architecting, code review, and critical decision making.
• Proven experience with 99.99% availability and enterprise apps.
• Hands-on with Pega Infinity production support and platform ops.
• Strong knowledge of Pega constructs: queues, agents, DDS, Kafka, APIs.
• GenAI tooling experience for incidents and automation.
• Proficiency in .NET and scripting (Python, Bash, PowerShell).
• Experience with observability platforms and CI/CD pipelines.

Responsabilidades

• Design architectures achieving 99.999% uptime for key systems.
• Define and track SLOs, SLIs, and error budgets.
• Build AI-powered self-healing, auto‑remediation and capacity planning.
• Provide production support for Pega Infinity applications.
• Lead incident triage, RCA, and runbook improvements with AI assistance.
• Develop AI agents for incident response and automation.
• Modernize monitoring, alerting, and deployment processes.
• Collaborate in architecture reviews and production readiness.

Conhecimentos

SRE/DevOps

Pega Infinity

GenAI tooling

CI/CD pipelines

Observability tools

Docker & Kubernetes

Cloud platforms

CS fundamentals

Formação académica

Bachelor's degree in Computer Science or equivalent

Ferramentas

Datadog

Splunk

Grafana

Jenkins

GitHub Actions

Kubernetes

Docker

Oracle

Mongo

SQL DBs

Descrição da oferta de emprego

Job Description -

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.

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

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

Qualifications and Experience

• 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

• 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