Centific | Site Reliability Engineering Manager

3 weeks ago


chennai, India Centific Full time

Centific is a Seattle-based tech company pioneering the future of AI one breakthrough at a time. Learn how we’re transforming the world through safe and scalable AI and empowering businesses to unlock the full potential of their data.



SRE Directo

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Key Responsibilities

:Strategic Leadership & Vision

:Lead and manage the Software Release Management function for all Data and AI products

Establish a centralized release management framework for AI and data products that scales with the growing product portfolio

Form and lead a high-performing Site Reliability Engineering (SRE) team to ensure the operational stability and performance of all AI and data-driven applications post-release

Collaborate with Product, Engineering and Operations teams to align release and SRE strategies with business objectives

.Release Planning & Coordination

:Oversee the full lifecycle of software and AI model releases, from planning and coordination to post-release evaluation

Develop and maintain a detailed release calendar that aligns with the timelines and priorities of various product teams

Coordinate release activities with multiple cross-functional teams, ensuring transparent communication of dependencies, risks, and milestones

Ensure that all releases are integrated seamlessly into production, minimizing downtime and disruptions to end users

.Site Reliability Engineering (SRE) Team Formation

:Hire, build, and lead the SRE team responsible for maintaining the reliability, scalability, and performance of all Data and AI products in production

Define the roles and responsibilities of the SRE team, ensuring clear alignment with the goals of product engineering and release management

Develop and implement SRE best practices, including incident response, root cause analysis, and proactive performance monitoring

Establish SLAs, SLOs, and SLIs (Service Level Agreements/Objectives/Indicators) to track and measure the reliability and performance of all services post-release

Collaborate with DevOps to ensure that automated CI/CD pipelines integrate seamlessly with SRE processes and monitoring systems

.Process Optimization & Automation

:Lead the automation of software release processes, with an emphasis on CI/CD pipelines for AI models, data pipelines, and cloud-based AI products

Develop infrastructure-as-code practices to improve the scalability and reliability of AI and data systems across production environments

Introduce tools for version control, model governance, and monitoring for MLOps and AI model management in production

Continuously improve operational procedures to reduce the number of incidents and optimize recovery time

.Risk & Quality Management

:Implement comprehensive quality assurance and validation processes to ensure that all AI models, data products, and software releases meet security, performance, and compliance requirements

Proactively identify and mitigate risks related to releases, AI model performance, and operational stability in production

Conduct post-release reviews and retrospectives to continuously improve both the release process and the reliability of products


.
Collaboration & Stakeholder Managemen

t:Serve as the central point of contact for release management and SRE-related matters, ensuring consistent communication between engineering, product teams, and key stakeholder

s.Facilitate cross-functional collaboration to ensure that releases and operational reliability goals are met efficiently and effectivel

y.Provide regular updates on release progress, system reliability, and any potential risks to executives and product leadershi

p.Innovation & Continuous Improvemen

t:Stay up to date with the latest trends in SRE, DevOps, AI/ML, and cloud operations, incorporating new tools and practices to improve the overall reliability and release processe

s.Drive the adoption of cutting-edge tools in MLOps, AI model deployment, and automated incident resolution to continuously optimize operations and model lifecycle managemen

t.Foster a culture of continuous improvement by encouraging feedback loops and metrics-driven decision-making across both the release management and SRE team

s.Qualification

s:Bachelor’s or Master’s degree in Computer Science, Data Engineering, AI/ML, or a related fiel

d.10+ years of experience in software release management, with at least 3-5 years in SRE or DevOps environments, preferably in AI or data-driven application

s.Proven experience building and managing both release management and SRE teams in complex, multi-product environment

s.Strong knowledge of AI/ML operations (MLOps), data pipeline management, and cloud-based AI product deployment

s.Expertise in release management tools (Jenkins, GitLab, Git, Jira) and SRE tools such as Prometheus, Grafana, Datadog, or similar monitoring system

s.Experience with cloud platforms (AWS, GCP, Azure), containerization (Kubernetes, Docker), and infrastructure automation tools (Terraform, Ansible

).Excellent problem-solving, organizational, and leadership skills, with a strong track record of driving continuous improvement in both release and operational reliability processe

s.Preferred Qualification

s:Experience deploying and maintaining large-scale AI/ML models in production environments, including monitoring, retraining, and operationalizatio

n.Familiarity with ITIL, MLOps, or DevOps frameworks and best practice

s.Knowledge of cloud-based services and tools specifically designed for AI/ML (e.g., AWS SageMaker, TensorFlow, PyTorch

).Demonstrated ability to manage incident response and root cause analysis in complex software ecosystem



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