Onsite Interview Site Reliability Engineer, AI & Agentic Systems

On-Site Interview: Site Reliability Engineer, AI & Agentic Systems _ Plano, TX Location: Plano, TX 9-month contract Work Schedule: Hybrid role requiring 3 days onsite per week in Plano, TX. Candidates must be able to attend an onsite interview in Plano, TX. Please target local candidates in the Dallas/DFW area. Interview Process: 2 Steps

• Virtual Interview
• Onsite Interview in Plano, TX

Work Authorization: Candidates must be authorized to work in the U.S. and can be H1-B, EAD-OPT, EAD-CPT, TN Visa, EAD-Green Card, Green Card, or U.S. Citizen.

As our SRE charter continues to evolve, this role demands strong hands-on ownership of production reliability and troubleshooting, coupled with advanced capabilities in AI- and agentic-driven automation and performance engineering.The Site Reliability Engineer will play a critical role in ensuring reliability, scalability, performance, and operational excellence of our platforms. The ideal candidate will leverage Azure-native AI services and agentic systems to reduce toil, improve incident response, and enable intelligent operations—while also driving performance testing practices to validate system resilience under load
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A DAY IN THE LI FEIn this role, you wil

• l…Own end-to-end reliability of large-scale, Azure-hosted production systems, ensuring high availability, fault tolerance, and graceful degradati
• onLead hands-on incident troubleshooting, root cause analysis (RCA), and post-incident reviews with actionable follow-u
• psBuild and operate resilient, scalable services on Microsoft Azure (AKS, App Services, Functions, Event Hubs, etc
• .)Design and maintain comprehensive observability platforms using Prometheus for metrics, Loki for log aggregation, Tempo for distributed tracing, and Grafana for dashboarding and alerti
• ngDesign, develop, and execute performance testing strategies for distributed systems and microservices, including load testing, stress testing, soak testing, and capacity planni
• ngIntegrate AI agents with Azure monitoring stack, CI/CD tooling, and incident management platfor
• msContribute to evolving SRE standards, tooling, operational processes, and knowledge ba

se
Reliability Engineering & Production Owners

• hipOwn end-to-end reliability of large-scale, Azure-hosted production systems, ensuring high availability, fault tolerance, and graceful degradat
• ionLead hands-on incident troubleshooting, root cause analysis (RCA), and post-incident reviews with actionable follow-
• upsDefine, measure, and enforce Service Level Indicators (SLIs), Service Level Objectives (SLOs), and error budgets aligned with business outco
• mesDrive proactive reliability improvements based on operational insights, failure mode analysis, and capacity plann
• ingParticipate in on-call rotations and take real-time ownership during production incide

nts
Platform & Automation Enginee

• ringBuild and operate resilient, scalable services on Microsoft Azure (AKS, App Services, Functions, Event Hubs, e
• tc.)Design and maintain comprehensive observability platforms using Prometheus for metrics, Loki for log aggregation, Tempo for distributed tracing, and Grafana for dashboarding and aler
• tingCreate automation to eliminate manual operational tasks and reduce Mean Time to Recovery (M
• TTR)Implement self-healing mechanisms, automated remediation workflows, and runbook automa
• tionManage and optimize API lifecycle and traffic management using Gravitee API Gat
• ewayDesign and implement durable, fault-tolerant workflows and microservice orchestration patterns using Temp
• oralAdminister and tune PostgreSQL databases for reliability, performance, and high availabi
• lityPartner with application and platform teams to improve service operability, deployment safety, and change manage

ment
Performance Testing & Load Engine

• eringDesign, develop, and execute performance testing strategies for distributed systems and microservices, including load testing, stress testing, soak testing, and capacity pla
• nningBuild and maintain performance test scripts and virtual user scenarios using Micro Focus LoadRunner and VuGen (Virtual User Gener
• ator)Analyze performance test results to identify bottlenecks, regressions, and scalability limits; produce clear reports with actionable recommenda
• tionsIntegrate performance testing into CI/CD pipelines to enable continuous performance validation and shift-left testing prac
• ticesEstablish and monitor performance baselines, benchmarks, and SLAs across critical service endpoints and user jou
• rneysCollaborate with development and architecture teams to resolve performance issues and optimize system throughput, latency, and resource utiliz

ationAI / Agentic Engineering (Azure F

• ocus)Design and implement AI-driven and agentic systems to enhance operational workflows and intelligent decision-m
• akingBuild intelligent automation for operational use cases, inclu
• ding:Incident triage, enrichment, and automated escal
• ationAlert correlation, deduplication, and noise redu
• ctionAutomated diagnosis and remediation of recurring fai
• luresLeverage Azure AI services (Azure OpenAI, Cognitive Services, Azure ML) for operational intelligence and predictive ins
• ightsIntegrate AI agents with Azure monitoring stack, CI/CD tooling, and incident management plat
• formsEnsure safe, reliable, and observable operation of AI-powered systems in production, including guardrails, fallback mechanisms, and audit t

rails
Collaboration & Technical Lead

• ershipAct as a reliability, performance, and automation champion across engineering
• teamsMentor junior SREs and influence adoption of best practices in reliability, observability, and performance engin
• eeringContribute to evolving SRE standards, tooling, operational processes, and knowledg
• e baseParticipate in architecture reviews and provide guidance on non-functional requirements (reliability, scalability, perfor

mance)
Core SRE

• Skills5+ years of experience in Site Reliability Engineering, DevOps, or Production Engineerin
• g rolesStrong hands-on experience in production troubleshooting of distributed systems a
• t scaleSolid understanding of Linux internals, networking (TCP/IP, DNS, HTTP, TLS), and system performance
• tuningDeep hands-on experience with Microsoft Azure (compute, networking, storage, managed service
• s, AKS)Strong knowledge of Kubernetes, container orchestration, Helm charts, and microservices archit
• ecturesProficiency in one or more programming languages: Python, Go, Java, or equ
• ivalentExperience with CI/CD pipelines (Azure DevOps, GitHub Actions) and Infrastructure as Code (Terraform, ARM Templates,

Bicep)
Observability & Mo

• nitoringHands-on experience building and operating observability stacks using Prometheus, Grafana, Loki, a
• nd TempoExperience with alerting strategies, SLI/SLO-based monitoring, and on-call incident ma

nagement
Performance Testing & Load En

• gineeringProven experience designing and executing performance and load testing for large-scale distributed app
• licationsHands-on proficiency with Micro Focus LoadRunner and VuGen for scripting virtual user scenarios, parameterization, correlation, and result
• analysisStrong understanding of performance testing methodologies: load testing, stress testing, endurance/soak testing, spike testing, and capacity
• planningAbility to analyze performance metrics (throughput, response time, error rate, resource utilization) and translate findings into engineerin
• g actionsExperience integrating performance tests into automated CI/CD

pipelinesPlatform & M

• iddlewareExperience with Gravitee or equivalent API gateway platforms for traffic management, rate limiting, and API lifecycle g
• overnanceHands-on experience with Temporal for workflow orchestration, durable execution, and distributed task m
• anagementStrong PostgreSQL administration skills, including query optimization, replication, backup/recovery, and performan

ce tuningAI / Agenti

• c SystemsHands-on experience building or integrating AI-powered automation in production env
• ironmentsExperience with agent-based systems, LLM-powered workflows, Retrieval-Augmented Generation (RAG), or intelligent a
• ssistantsFamiliarity with Azure-based AI and ML services (Azure OpenAI, Cognitive Services,
• Azure ML)Understanding of reliability, safety, observability, and operational challenges of AI systems in p

roduction