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AI Ops Technical Leader

Lingarogroup
CompanyLingarogroup
CategoryData & Analytics
LocationPhilippines
RemoteRemote
EmploymentFull-time
LevelNot stated
SalaryNot stated by the employer
Posted12 Feb 2026
Last verified30 Jul 2026
SourceEmployer career page (lever)
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Description
As AI Ops Technical Leader, you drive the intelligent transformation of operations support. This player-coach role combines hands-on technical delivery, team leadership, and AI architecture governance to achieve operational excellence. You apply deep technical expertise and strategic leadership to design, build, and evolve AI and data solutions that improve incident management, major incident response, problem management, change enablement, service desk support, observability, and overall operational resilience.   What You'll Be Doing:   Hands-on Data & AI Solutions for Operations Support ·       Lead and contribute to high-impact data and AI initiatives that improve operations support outcomes, including real-time incident enrichment, automated root‑cause analysis, predictive alerting, ticket clustering and auto-triage, change risk scoring, knowledge mining, and intelligent runbooks. ·       Design and deliver scalable AI-enabled features embedded into operations support platforms such as ServiceNow, Jira Service Management, monitoring/observability tools, and ITSM systems. ·       Ensure all solutions meet strict operational SLAs for reliability, low latency, auditability, explainability, and zero-downtime deployment. ·       Stay up to date with emerging AIOps tools, research, and trends, and apply them to enhance operations support.   AIOps Tools & Platform Leadership ·       Lead the architecture, development, and continuous improvement of internal AIOps platforms and reusable components supporting operations teams. ·       Integrate AIOps tools with ITSM systems, observability platforms (Prometheus, Grafana, ELK, Dynatrace, Splunk), ticketing systems, and automation frameworks. ·       Apply best practices in MLOps/AI Ops tailored to production environments: model monitoring, drift detection, automated rollback, performance checks, and cost optimization at scale.   AI Technical Leadership for Operations Support Initiatives ·       Serve as the principal AI technical authority for operations support transformation programs across service operations, NOC, support desks, infrastructure operations, and reliability engineering. ·       Lead technical discussions, architecture reviews, proof of concepts, vendor evaluations, and solution selection involving AI for operations. ·       Identify, prioritize, and drive high‑value AI use cases focused on reducing MTTR/MTTD, automating L1 triage, predicting major incidents, generating post‑mortems, optimizing shift handovers, and enabling proactive operations.   Team & People Leadership ·       Build, mentor, and lead a high-performing squad of AIOps specialists focused on measurable operations support improvements. ·       Foster a culture of experimentation, production‑first thinking, and commitment to operational impact—reduced toil, faster resolution, and higher availability. ·       Provide technical coaching, conduct design/code reviews, and guide career development with emphasis on operations and support domain expertise.   Stakeholder & Cross-Functional Collaboration ·       Work closely with operations support leaders, incident managers, service owners, reliability engineers, ITSM teams, infrastructure groups, and other stakeholders to align AI solutions with operational needs. ·       Collaborate deeply with DS&AI Competency teams to ensure high-quality, scalable, and sustainable AI delivery.     What We’re Looking For: ·       Strong background indata engineering, AI/ML, or operations support technology, including technical leadership in operations, IT, or service environments. ·       Proven track record delivering production AI/ML/data solutions that improve MTTR, MTTD, availability, and ticket deflection. ·       Hands-on expertise with Python, Spark, Kafka, Airflow, cloud data platforms, PyTorch/TensorFlow, LLMs, and integrat
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