SRE Leader

ExaTech Inc; Atlanta (GA); Hybrid; USD 150,000 - 190,000; Full time

Job summary

ExaTech Inc. seeks an SRE Architect in Atlanta, GA, to lead reliability strategy, architecture, and platform design. The role drives scalable cloud patterns, codified standards, and proactive observability across services, guiding teams toward resilient operation.

You will mentor engineers, shape SRE practices, and oversee postmortems and incident response while advancing AI-powered reliability initiatives and scalable automation.

Qualifications

• Proven experience designing reliable, scalable systems.

Responsibilities

• Reliability Strategy & Design: Architect highly available infrastructure and patterns on AWS.

Skills

SRE architecture

Cloud AWS

Observability

Automation

AI/ML in Ops

Kubernetes

Python

Tools

Dynatrace

Prometheus

Grafana

ELK

OpenTelemetry

CI/CD

IaC

Job description

CANDIDATES OPEN TO RELOCATE FROM NEARBY LOCATIONS (AL, NC, SC, TN, Jacksonville)

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Atlanta GA [hybrid]

Contract

50% Hybrid – Work From Office Schedule

The role follows a 50% hybrid work model. Employees are required to work from the office for 5 consecutive business days, from Wednesday through the following Tuesday, on alternate weeks.

Role Summary:

As an SRE Architect, you will be a pivotal technical leader responsible for designing, building, and evolving the foundational systems and practices that ensure the reliability, scalability, performance, and efficiency of our critical services. Moving beyond day-to-day operations, you will focus on the strategic architectural direction of SRE function, defining standards, blueprints, and frameworks that enable development teams and fellow SRE operations team to build and operate highly resilient systems. Leverage deep expertise in software engineering, distributed systems, cloud infrastructure, and SRE principles to influence technology choices, establish best practices, and foster a proactive culture of reliability across the organization and much beyond observability pillar.

Key Responsibilities:

• Reliability Strategy & Design: Architect and design highly available, scalable, secure, and cost-effective infrastructure and application patterns on AWS
• Define and evangelize SRE best practices, standards, and blueprints for service design, deployment, monitoring, and operational readiness across the engineering organization
• Review current observability implementation to identify gaps and define steps to reach next level maturity of observability setup to provide deep insights into system health and behaviour
• With overall maturity lead the definition and implementation strategy for Service Level Indicators (SLIs), Service Level Objectives (SLOs), and Error Budgets for critical services
• Platform Architecture & Automation: Design solutions to systematically reduce operational toil through automation and improved system design
• Evaluate current SRE tools and automation frameworks (e.g., CI/CD pipelines, Infrastructure as Code modules, automated incident remediation, chaos engineering platforms) and suggest enhancement that will help overall enhancement of capability
• Evaluate, prototype, and recommend new technologies, tools, and methodologies to enhance system reliability, developer productivity, and operational efficiency
• Technical Leadership & Consultation: Act as a senior technical advisor and subject matter expert on reliability, scalability, and performance for development and platform teams
• Provide architectural guidance during the design phase of new services and features to ensure reliability principles are embedded early (shift-left)
• Mentor and coach other SREs and engineers, fostering technical excellence and adherence to SRE principles
• Lead architectural reviews and production readiness assessments for critical systems
• Resilience:
• Lead blameless postmortems for significant incidents, ensuring root causes are identified and systemic architectural improvements are prioritized and implemented
• Architect and advocate for resilience patterns (e.g., circuit breaking, rate limiting, graceful degradation, chaos engineering) within applications and infrastructure.
• Define and drive the organization's AIOps strategy, leveraging AI/ML and Generative AI capabilities to improve observability, incident management, root cause analysis, capacity forecasting, and operational efficiency.
• Design and implement intelligent operational platforms that use AI agents, knowledge graphs, telemetry analytics, and automation frameworks to proactively detect, diagnose, and remediate production issues.
• Architect AI-powered production intelligence solutions that correlate logs, metrics, traces, configuration data, deployment events, CMDB, cloud services, and dependency mappings to generate actionable operational insights.
• Establish architectural patterns for AI-assisted incident triage, impact analysis, service dependency intelligence, and automated remediation workflows.
• Lead the adoption of Agentic AI frameworks, MCP (Model Context Protocol) integrations, and enterprise AI platforms to improve developer productivity and operational effectiveness.
• Define governance frameworks for AI usage in production operations including explainability, auditability, security, risk management, and human-in-the-loop controls.
• Partner with Data Engineering, Platform Engineering, and Application teams to develop AI-enabled reliability use cases and operational copilots.
• Establish mechanisms to continuously evaluate and improve AI model effectiveness, hallucination mitigation, operational accuracy, and reliability of AI-driven decision making.

Required Qualifications:

• Proven experience in an architectural role, designing solutions for reliability, scalability, and performance
• Deep understanding and practical application of SRE principles (SLIs/SLOs, error budgets, toil reduction, automation, incident management, postmortems)
• Experience designing and implementing AIOps, AI-powered observability, or intelligent automation solutions to improve incident detection, root cause analysis, operational efficiency, and service reliability.
• Working knowledge of Generative AI, AI agents, MCP (Model Context Protocol), RAG architectures, and enterprise AI platforms, with experience building or operationalizing AI-enabled engineering tools in production environments.
• Expertise in cloud computing platforms (e.g., AWS) including infrastructure, networking, and security services
• Strong experience with containerization and orchestration technologies (Kubernetes, Docker, serverless computing)
• Solid experience designing and implementing observability solutions (e.g., Dynatrace, Prometheus, Grafana, ELK/EFK Stack, Jaeger, OpenTelemetry)
• Strong programming/scripting skills (e.g., Python, Go, Bash) for automation and tool development
• Excellent analytical, problem-solving, and strategic thinking skills.
• Strong communication, collaboration, and leadership skills with the ability to influence technical direction across teams

Preferred Qualifications:

• Experience designing and implementing chaos engineering practices and platforms