Senior Architect, ML Engineering
Icertis
The Engineer will be responsible for handling complex business-critical incidents across large-scale AI/ML-driven SaaS products in a B2B enterprise environment. Serving as the final technical escalation point, this role ensures the high availability, performance, and compliance of customer-facing platforms running on Microsoft Azure. It demands a strong blend of cloud-native troubleshooting expertise, AI/ML workload insight, and enterprise-grade operational practices.
Icertis is the global leader in AI-powered contract intelligence. The Icertis platform revolutionizes contract management, equipping customers with powerful insights and automation to grow revenue, control costs, mitigate risk, and ensure compliance - the pillars of business success. Today, more than one third of the Fortune 100 trust Icertis to realize the full intent of millions of commercial agreements in 90+ countries.
Who we are: Icertis is the only contract intelligence platform companies trust to keep them out in front, now and in the future. Our unwavering commitment to contract intelligence is grounded in our FORTE values—Fairness, Openness, Respect, Teamwork and Execution—which guide all our interactions with employees, customers, partners, and stakeholders. Because in our mission to be the contract intelligence platform of the world, we believe how we get there is as important as the destination.
Icertis, Inc. provides Equal Employment Opportunity to all employees and applicants for employment without regard to race, color, religion, gender identity or expression, sex, sexual orientation, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state and local laws. Icertis, Inc. complies with applicable state and local laws governing non-discrimination in employment in every location in which the company has facilities. If you are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to careers@icertis.com or get in touch with your recruiter.
Required Skills & Experience
Development and troubleshooting skills on the Microsoft platform, with expertise in C#, ASP.NET, MVC, SQL, JQUERY, Stored Procedures, Azure. Python skills will be an 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, Elastic Search/Kibana, Open Telemetry, and Azure Monitor.
Service Management: Strong knowledge of ITSM processes (incident, problem, change).
Experience: 12–15 years in technical architect engineering roles, with at least 2+ years in senior technical leadership positions 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.
Desired Attributes
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.
Act as the highest-level technical authority for critical issues impacting AI/ML SaaS products.
Develop a detailed technical understanding of AI applications and services and be equipped to fix hands-on issues in any area.
Perform deep-dive diagnostics across microservices, APIs, AI/ML pipelines, and Azure resources.
Lead root cause analysis (RCA), create 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 resolution 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. Feed field issues into the product backlog.
Implement and fine-tune monitoring using Datadog, Elastic Search/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.
Provide mentoring and technical guidance to junior engineers and operational teams.