Architect, Applied AI Engineering

1 day ago

Pune, Maharashtra, India Icertis Full time ₹ 12,00,000 - ₹ 24,00,000 per year
Description

  • Act as the highest-level escalation for L3/L4 issues impacting AI/ML SaaS products.

  • Develop a detailed technical understanding of AI Apps and services and be equipped to hands-on fix issues in any area.

  • Perform deep-dive diagnostics across microservices, APIs, AI/ML pipelines, and Azure resources.

  • Lead root cause analysis (RCA), create ServiceNow incident/problem records, and implement permanent fixes.

  • Ensure adherence to SLAs and SLOs for enterprise customers.

  • Interface with Partners, Professional services and Customers during escalations, lead debugging and provide resolutions plans.

  • Support and troubleshoot AI/ML inference services, model deployments, and data pipelines.

  • Work with Azure Machine Learning, Azure Kubernetes Service (AKS), and Azure Data/Storage services.

  • Collaborate with data scientists and engineering teams on performance optimization and retraining impacts. Feeback field issues into product backlog.

  • Implement and fine-tune monitoring using Datadog, ElasticSearch/Kibana, and Azure Monitor.

  • Set up and maintain alerting for anomaly detection in AI/ML workloads.

  • Partner with engineering, DevOps, and SRE teams to improve architecture and prevent recurring incidents.

  • Create and maintain detailed runbooks, playbooks, and knowledge base articles for ServiceNow.

  • Provide mentoring and technical guidance to L1/L2 teams.

  • Excellent problem-solving and incident management skills under pressure.

  • Strong customer communication for enterprise B2B clients.

  • Ability to collaborate with AI engineers, data scientists, and SRE/DevOps teams.

  • Passion for automation and continuous improvement.

Responsibilities

  • Development and troubleshooting skills on the Microsoft platform, with expertise in C#,ASP.NET, MVC, SQL, JQUERY, Stored Procedures, Azure. Python skills will added advantage.

  • Database: SQL debugging, query tuning; exposure to Cosmos DB or PostgreSQL preferred.

  • Cloud & Infra: Deep hands-on expertise in Microsoft Azure (AKS, App Services, Functions, Storage, Networking), CI/CD pipelines.

  • AI/ML: Understanding of ML model deployment, inference pipelines, vector stores, RAG, and GPU/CPU optimization.

  • Observability & Logging: Proficiency with Datadog, ElasticSearch/Kibana, OpenTelemetry, and Azure Monitor.

  • Service Management: Strong knowledge of ServiceNow ITSM (incident, problem, change).

Experience: 12–15 years in technical/production support, with at least 4+ years in L3 or senior escalation roles in a cloud/SaaS environment.

   

Qualifications

B.E./B.Tech/MCA or equivalent degree. Certifications like Microsoft Azure Solutions Architect, Azure DevOps Engineer, or Datadog Observability are a plus.

 

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