Senior Site Reliability Engineer
Jones Lang LaSalle Incorporated
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Job summary
Jones Lang LaSalle Incorporated in Bengaluru seeks a Senior Site Reliability Engineer to lead the design and operation of scalable, AI-enhanced infrastructure on AWS, with IaC using Terraform. You will drive reliability, observability, and incident response across multi-account deployments.
We value collaboration with development and data teams, mentoring peers, and applying AI-driven automation to reduce toil while improving MTTR and system resilience.
Qualifications
- Bachelor's degree in Computer Science, Engineering, Data Science, or related field (or equivalent).
- 5+ years in DevOps or Site Reliability Engineering with incident leadership.
- Experience integrating AI/ML into operational workflows.
Responsibilities
- Lead design and implementation of IaC-based infrastructure using Terraform and Kubernetes.
- Oversee reliability, observability, monitoring, and AI-enhanced operations.
- Manage incident response, post-mortems, and MTTR improvements.
Skills
Education
Tools
Job description
JLL empowers you to shape a brighter way. Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward.
We are seeking a skilled and experienced Senior Site Reliability Engineer to join our dynamic team. As a Senior SRE, you will be responsible for leading the implementation and maintenance of reliable, scalable infrastructure and deployment pipelines using Terraform and Infrastructure as Code practices across multiple AWS Cloud accounts. You will play a critical role in ensuring the efficiency, reliability, observability, and scalability of our systems while fostering a culture of collaboration, automation, and continuous improvement through SRE principles. This role requires understanding of how your area integrates with development teams and the ability to translate business continuity needs into technical reliability requirements, leveraging Agentic AI capabilities to enhance operational excellence.
- Act as resource for less experienced colleagues in troubleshooting and reliability best practices.
- Act as informal coach and deliver knowledge-sharing sessions on incident response, system design, and AI-enhanced operational practices.
- Lead medium projects with manageable risks and guide team members on operational procedures.
- Provide technical guidance on reliability engineering principles and AI/ML integration opportunities.
- Share expertise in automation, monitoring, and AI-driven operational improvements with team members.
- Design independently for complex infrastructure items following Infrastructure as Code (IaC) best practices using Terraform, Docker, Kubernetes, and various scripting languages.
- Evaluate others' designs using reliability engineering methodologies and provide constructive feedback.
- Consider scalability, maintenance, and operational experience in all design decisions.
- Integrate AI and machine learning capabilities into infrastructure solutions for improved reliability and efficiency.
- Lead incident response processes and apply AI-assisted diagnostics to accelerate resolution.
- Design monitoring solutions that leverage AI for anomaly detection and predictive alerting.
- Implement intelligent automation using AI-driven decision support for routine operational tasks.
- Establish and monitor Service Level Objectives (SLOs), Service Level Indicators (SLIs), and error budgets to measure and improve system reliability and performance.
- Design and implement comprehensive monitoring, alerting, logging, and observability solutions using AI/ML for proactive issue identification and automated anomaly detection.
- Lead incident response efforts, conduct blameless post-mortems, and implement preventive measures to reduce Mean Time to Recovery (MTTR).
- Solve medium to high complexity infrastructure problems using technical experience, judgment from multiple sources, and AI-powered analytics.
- Take new perspectives on existing reliability solutions and identify opportunities for AI enhancement.
- Apply AI for log analysis, pattern recognition, and root cause analysis to improve incident resolution speed.
- Implement basic AIOps practices to enhance operational intelligence.
- Collaborate with development, operations, product, data engineering, and business teams to understand requirements and implement reliability standards.
- Translate business continuity needs into technical reliability requirements.
- Apply domain expertise using AI-driven monitoring and automation to solve operational challenges.
- Work closely with development teams to integrate SRE best practices including toil reduction, capacity planning, and chaos engineering.
- Partner with data science teams to understand and operationalize ML model reliability requirements.
- Drive adoption of AI-enhanced DevOps practices within immediate operational teams.
- Develop and maintain runbooks, documentation, and knowledge bases to support operational excellence.
- Stay current with the latest trends, tools, and technologies in SRE, DevOps and AIOps fields.
- Contribute to improving system reliability and enterprise operational efficiency within established frameworks.
- Actively contribute towards enterprise-wide reusable reliability solutions incorporating AI capabilities.
- Experiment with AI-powered tools for automation, monitoring, and documentation generation.
- Share learnings about AI/ML applications in DevOps with the broader team.
- Bachelor's degree in Computer Science, Engineering, Data Science, or a related field (or equivalent experience).
- 5+ years of experience working in DevOps or Site Reliability Engineering roles.
- Proven experience in troubleshooting complex infrastructure issues and leading incident response.
- Demonstrated experience integrating AI/ML capabilities into operational workflows.
- Strong proficiency in Terraform and Infrastructure as Code principles for infrastructure provisioning and management.
- Extensive experience with Amazon Web Services (AWS), including EC2, VPC, S3, IAM, CloudWatch, CloudFormation, and familiarity with SageMaker.
- In-depth knowledge of RDS and its various database engines (e.g., MySQL, PostgreSQL, Oracle) for database provisioning, management, and performance optimization.
- Solid understanding of Kubernetes for container orchestration, management, and resilience patterns.
- Expertise in monitoring AND automation or specialist in one area with AI integration capabilities.
- Hands‑on experience with Agentic frameworks and tools (e.g., Langgraph, Langchain and openai).
- Experience implementing AI-powered monitoring and observability solutions for anomaly detection and predictive alerting.
- Understanding of AIOps practices and platforms for operational intelligence.
- Proficiency in using AI for log analysis, pattern recognition, and automated diagnostics.
- Knowledge of machine learning techniques for capacity planning and performance forecasting.
- Familiarity with MLOps concepts for reliable model deployment and monitoring.
- Experience with AI-powered automation tools and intelligent alerting systems.
- Continuous learner with passion for staying updated with SRE principles, reliability patterns, DevOps trends, and proactive in exploring new AI technologies and their applications in DevOps and SRE.
- Familiarity with application security best practices, tools, and compliance frameworks.
- Understanding of DevSecOps practices and AI-powered security monitoring.
- Experience with GitHub Actions and Jenkins or similar tools for workflow automation and CI/CD.
- Experience with ArgoCD.
- Experience with cloud-native operational practices and multi-cloud environments.
- Track record of contributing to enterprise-wide reusable reliability solutions.
- Familiarity with AI-powered chatbots or virtual assistants for incident management.
At JLL, we make sure that you become the best version of yourself by helping you realize your full potential in a fully entrepreneurial and inclusive work environment. If you harbor passion for learning and adapting new technologies, including AI and machine learning, JLL will continuously provide you with platforms to enrich your technical domains. We will empower your ambitions through our dedicated Total Rewards Program, competitive pay and benefits package.
This role aligns with JLL's P3 Senior Site Reliability Engineer level, offering opportunities to design complex infrastructure solutions, lead incident response processes, integrate AI/ML capabilities into DevOps practices, and act as a technical resource and mentor while contributing to operational excellence through intelligent automation.
Location: On-site – Bengaluru, KA
Scheduled Weekly Hours: 40
Jones Lang LaSalle (“JLL”) is an Equal Opportunity Employer and is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process – including the online application and/or overall selection process – you may email us at HRSCLeaves@jll.com. This email is only to request an accommodation.
Jones Lang LaSalle (JLL), together with its subsidiaries and affiliates, is a leading global provider of real estate and investment management services. We take our responsibility to protect personal information provided to us seriously. Generally the personal information we collect from you are for the purposes of processing in connection with JLL’s recruitment process. We endeavour to keep your personal information secure with appropriate level of security and keep for as long as we need it for legitimate business or legal reasons. We will then delete it safely and securely. For more information about how JLL processes your personal data, please view our Candidate Privacy Statement. For additional details please see our career site pages for each country. Jones Lang LaSalle (“JLL”) is an Equal Opportunity Employer and is committed to working with and providing reasonable accommodations to individuals with disabilities.
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