Senior Support Lead

Technology, Data & Digital · Data, AI & Analytics · Data Science · Machine Learning · DevOps

In short

Der AI Ops Support Engineer ist für die tägliche operative Gesundheit, Überwachung und L2/L3-Unterstützung von Produktions-Generative-AI- und Machine-Learning-Lösungen verantwortlich. Die Rolle konzentriert sich auf die Aufrechterhaltung der Stabilität, Verfügbarkeit und Leistung von AI/ML-Plattformen durch proaktive Überwachung der Systemgesundheit, Triage von Vorfällen und Einhaltung definierter Service Level Agreements (SLAs).

Responsibilities

Perform daily operational health checks, service validations, and active monitoring of production GenAI and ML workloads.
Monitor established observability dashboards (Datadog, Dynatrace, etc.) to track model drift, latency, API consumption, token usage, and system costs.
Respond immediately to system-generated alerts regarding threshold breaches, data quality issues, and infrastructure failures.
Triage, investigate, and resolve incident tickets related to AI/ML services within specified SLAs.
Follow defined escalation paths to engage L3 engineers, Data Scientists, or Platform teams for complex, systemic issues.
Assist in gathering logs, metrics, and event timelines to support Root Cause Analysis (RCA) and document incident reports.
Support the deployment of model upgrades, prompt adjustments, and system patches.
Conduct post-deployment validation and regression testing using operational runbooks.
Monitor scheduled data pipelines (such as Databricks jobs and SQL warehouses) to ensure continuous training data flow and resolve minor job failures.
Execute standard automated scripts to resolve repetitive issues and recover failed services.
Write and maintain basic Python or Bash scripts to automate routine manual tasks, log parsing, and operational checks.
Document incident resolution steps, update troubleshooting runbooks, and draft new standard operating procedures (SOPs).
Maintain accurate records of all incidents, service requests, and operational actions within the ticketing system.

Requirements

Fundamental understanding of Generative AI, LLMs, prompt engineering, Retrieval-Augmented Generation (RAG), and MLOps lifecycles.
Experience utilizing APM and observability platforms (e.g., Datadog, Dynatrace, New Relic) to monitor application logs and system metrics.
Hands-on experience with Google Cloud Platform (GCP) services (Vertex AI, GKE, Cloud Functions, BigQuery, MemoryStore).
Proficiency in Python and Bash for automating routine operational tasks and querying APIs.
Familiarity with Databricks environments (managing job runs, clusters, and catalog accesses) and basic SQL querying.
Solid understanding of ITIL-based framework processes, specifically Incident, Problem, and Change Management.
Proven ability to work under SLA-driven environments, prioritizing tickets and tasks based on business impact.
Excellent written and verbal communication skills to clearly document technical issues and coordinate with cross-functional support tiers.
3–5 years of experience.

Benefits

You'll supercharge your potential.
You'll find your career.
And you'll find your spark.
All at a place that knows that helping its customers stay on top starts by putting its people first.

Skills

DatadogDynatraceNew RelicGCPVertex AIGKECloud FunctionsBigQueryMemoryStorePythonBashDatabricksSQLITIL

#AI Ops#Support Engineer#Generative AI#Machine Learning#MLOps#Cloud#Python#Bash#Databricks#GCP#ITIL

About HCLTech

Supercharging progress through technology and innovation

HCLTech is a global technology company, home to 219,000+ people across 54 countries, delivering industry-leading capabilities centered around digital, engineering and cloud, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending September 2022 totaled $12.1 billion. To learn how we can supercharge progress for…

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