Principal Engineer

About CBRE:
CBRE Group, Inc. is the world's largest commercial real estate services and investment firm, with a revenue of $40.55 billion (as recorded on December 31, 2025) and more than 155,000 employees (including Turner & Townsend employees) serving clients in more than 100 countries. CBRE has been on the Fortune 500 list each year since 2008, reaching #118 on the 2026 list, its highest ranking yet.

Job Role:

We are seeking a Principal Software Engineer to serve as the technical authority for AIOps, intelligent automation, and AI-first engineering across the enterprise application portfolio. The role architects agentic AI and automation solutions, sets enterprise reliability and observability standards, and leads cloud-native engineering practice at scale.
The role is deliberately technology-agnostic. The candidate will lead automation and application delivery across Power Platform, Google Cloud, and full-stack engineering, choosing the right approach for each use case while holding one consistent bar for governance, security, and reliability. Forward-Deployed AI Engineering is central to the work: partnering directly with business teams to prototype, deploy, and operationalize Generative AI, AI agents, and automation frameworks in production.
The successful candidate brings hands-on depth in AWS, Azure, or GCP, infrastructure as code using Terraform, modern CI/CD pipelines, and observability platforms, together with a track record of leading AIOps, SRE, platform engineering, and enterprise automation programs. This role will set engineering standards, mentor senior engineers, and drive operational excellence across the group.

Job Title: Principal Software Engineer
Job Location: Hyderabad/Gurugram/Noida
Start Date: As soon as possible

Key Responsibilities:

• Define and drive the technical roadmap for automation and Agentic AI adoption, partnering with engineering and product teams to reduce manual toil and accelerate self-healing operations.
• Architect end-to-end AIOps solutions integrating ServiceNow, Datadog, and AI/ML-based event correlation to drive intelligent incident detection and automated remediation across the enterprise application portfolio.
• Lead automation delivery independent of any specific technology, applying Power Platform, Google Cloud, or full-stack engineering as the use case demands, with consistent governance across all of them.
• Lead cloud and DevOps architecture initiatives spanning CI/CD, infrastructure-as-code, and container orchestration to ensure scalable, secure, and cost-optimized delivery.

General Responsibilities:

• Participate in code and architecture reviews, ensuring adherence to engineering best practices, coding standards, and design patterns.
• Collaborate with cross-functional teams in product, QA, and operations to translate business requirements into scalable technical solutions.
• Own technical documentation, including architecture decision records (ADRs), design specifications, and operational runbooks.
• Stay current with emerging technologies and industry trends, evaluating their applicability to the organization's technology roadmap.
• Contribute to technical hiring, including interviewing candidates and helping shape engineering competency frameworks.
• Champion a culture of engineering excellence, quality, and continuous improvement across teams.

AIOps and Intelligent Automation:

• Architect intelligent alerting, event correlation, and anomaly detection capabilities to reduce noise, accelerate root-cause analysis, and enable automated remediation.
• Lead design and adoption of agentic and generative AI-powered automation (Now Assist-style copilots, autonomous agents) using platforms such as ServiceNow, Google Gemini, or equivalent large language models (LLMs).
• Establish reusable automation frameworks, libraries, and governance standards to scale intelligent automation adoption across engineering teams.
• Evaluate and integrate a broad range of AIOps and observability platforms beyond a single vendor stack, including Splunk, Dynatrace, New Relic, and Prometheus/Grafana, selecting the right tool for each use case.
• Architect automation and orchestration workflows using engines such as Apache Airflow or Temporal, alongside a range of LLM providers such as OpenAI, Azure OpenAI, AWS Bedrock, or Anthropic Claude, keeping the architecture provider-agnostic.
• Embed directly with business and operations teams to find high-value AI use cases, then build working prototypes in weeks against their real data and workflows.
• Own the path from prototype to production, covering hardening, evaluation harnesses, monitoring, cost controls, and handover to the platform teams.
• Design and tune agentic workflows, retrieval pipelines, and prompt architectures, measuring accuracy, latency, and cost per outcome rather than demo quality.
• Define guardrails for enterprise AI use, including data handling, access control, human review checkpoints, and model fallback paths.
• Feed field learnings back into reusable frameworks, patterns, and reference implementations so the wider engineering group can reuse them without an FDE present.

Cloud, DevOps & SRE Leadership

• Design and review cloud-native and hybrid architectures (AWS, Azure, GCP) for scalability, resilience, and cost optimization, leading migration and modernization initiatives including containerization and infrastructure-as-code.
• Define and evolve CI/CD pipelines and DevSecOps standards, embedding security and compliance checks into the delivery pipeline.
• Act as the SRE technical authority, establishing SLIs, SLOs, and error budgets in partnership with engineering and product teams to drive a reliability-first culture.
• Lead capacity planning, failure mode analysis, and service dependency mapping to proactively eliminate toil and reduce MTTR across critical production systems.
• Drive blameless post-incident reviews and continuously refine on-call practices, runbooks, and escalation paths to strengthen organizational resilience.

Key Requirements:
12+ years of software engineering experience, including 3+ years in a principal or staff-level architecture role.
Bachelor's degree in Computer Science, Information Technology, or a related field; advanced degree preferred.
Minimum 5 years of hands-on expertise architecting AIOps and intelligent automation solutions in large-scale production environments.
¢ Proven track record of leading automation programs: defining reusable frameworks, driving adoption, and measuring operational impact at the organizational level.
¢ Deep knowledge of ITSM frameworks; experience integrating AIOps and automation practices with ServiceNow or equivalent platforms.
¢ Expert-level proficiency in AIOps tooling, including event correlation, anomaly detection, and intelligent alerting (Datadog, ServiceNow, or equivalent).
¢ Strong expertise in agentic and generative AI, including LLM-based copilots, orchestration frameworks, and prompt-driven automation.
¢ Experience designing and implementing infrastructure-as-code using Terraform (or equivalent) for cloud and platform configuration management.
¢ Proficiency in CI/CD pipeline design and automation (Jenkins, GitHub Actions, Azure DevOps, or equivalent).
¢ Strong experience with cloud platforms (AWS, Azure, or GCP), including cloud-native architecture, cost optimization, and reliability patterns.
¢ Hands-on experience with containerization and microservices architectures (Kubernetes, Docker, service mesh).
¢ Demonstrated ability to mentor and upskill senior and staff engineers on architecture, automation, and DevOps best practices.
¢ Familiarity with observability and monitoring standards (OpenTelemetry, Datadog, or equivalent) to support intelligent automation.
¢ Proficiency in scripting and programming (Python, Java, or Node.js) for building automation tooling and platform integrations.
¢ Strong analytical and problem-solving skills with an ability to diagnose complex distributed system and automation failures.
¢ Exceptional communication and stakeholder management skills; ability to translate technical architecture decisions for executive audiences.
¢ Experience integrating automation and AIOps platforms with ITSM tools (ServiceNow) for automated alerting, ticketing, and incident correlation.
¢ Strong grounding in Site Reliability Engineering (SRE) principles, including SLIs/SLOs, error budgets, blameless postmortems, and toil reduction at scale.
¢ Demonstrated experience in incident command and on-call leadership, including capacity planning and failure mode analysis for large-scale distributed systems.

Must have Skills:
¢ Expert-level proficiency in AIOps and intelligent automation, with working knowledge of agentic and Generative AI platforms.
¢ Demonstrated ability to drive end-to-end delivery of AI-first solutions, translating strategic objectives into production-ready Generative AI, Agentic AI, and automation platforms at enterprise scale.
¢ Proven principal-level technical ownership: demonstrated experience architecting and scaling automation, cloud, and DevOps solutions for critical production systems.
¢ Strong technical leadership capabilities: ability to drive architecture reviews, mentor engineers, and align cross-functional teams around a technical roadmap.
¢ Hands-on experience with cloud platforms (AWS, Azure, or GCP) and containerized environments (Kubernetes, Docker).
¢ Proven Site Reliability Engineering (SRE) experience: capacity planning, incident command, and reliability engineering for critical production systems at scale.

Preferred Certifications

• Azure/AWS/GCP Professional Cloud Certifications, Terraform Associate, Kubernetes (CKA/CKAD), ITIL 4, SRE Foundation
• AI Engineering/Generative AI Certifications,
• Power Platform, Google Cloud, ServiceNow, or full-stack development certifications, and Observability/AIOps certifications such as Datadog, Dynatrace, Splunk, or ServiceNow ITOM.

Reference Links:
CBRE D&T LINKS -

• https://www.youtube.com/watch?v=Lj8P5q2RMWY
• https://www.forbes.com/sites/peterhigh/2019/08/12/cbres-digital-and-technology-chief-on-why-these-roles-should-be-combined/#4fdfefa15692

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