HCLTech
Website:
hcltech.com
Job details:
Role: Technical Specialist - 10 - 18 Yrs Experience
Section Title: Job Summary
Job Summary
Job Title:AI Operations ManagerJob LevelLevel 3Duties and ResponsibilitiesLead production operations and continuous improvement for AI applications post‑deployment, driving automation to enhance reliability, scalability, and SLA adherence.
Partner with Application Managed Support (AMS) teams to transition high‑volume, repeatable support tickets, improving operational efficiency and reducing incident resolution time.• Leads production support processes after go-live of AI COE led deployments.
• Identifies all applicable support scenarios, leads ServiceNow ticket form creation, continuously tries to reduce set SLAs for resolution of tickets raised through automation and partnering with AMS team.
• Participate in post-deployment support planning (hypercare), SLA planning, triaging ServiceNow tickets, surfacing engineering and devlopment related work items needed, and operationalizing SOPs.
• Aim for reduction in overall ticket volume, ensuring higher rates of First Contact Resolution.
What Success Looks Like:
• Can accurately plan end-to-end support processes after go-live of AI COE applications.
• Automation focused mindset with strong initiative to reduce SLAs and improve support related metrics.
• Effective in building partnerships with cross functional and downstream support teams.
•Knowledge of handling support process of AI applications where deterministic behavior may be hard to traceback.
Years of Experience1-6 years (Given recency of AI applications, experience will not be the primary criteria for deciding level)
Must HaveNice to HaveDomain Expertise
CS/Engineering degree or bootcamp (with strong software projects).
Experience in AI/ML, Generative AI, data, or analytics software.
Experience in operations for AI products and projects atleast spanning a year
Technical / Functional SkillsCompetence in Python / Node.JS, and git.
Competence in defining SLAs
Experience with cloud PaaS, scripting, and infrastructure-as-code concepts.
AI/ML Ops
Project Experience
Must have managed post-deployment operations of at least one AI enabled product
Using automation scripts to improve support processes
Strong focus on operational metrics improvement
CertificationsAWS Cloud Practitioner, DevOps or AI/ML certification.X
Section Title: Key Responsibilities
Key Responsibilities
1. To architect| design and develop (through Team) solution for product/project & sustenance delivery
2. To support as an SME
3. To ensure knowledge up-gradation and work with new technologies so that the solution is current and meets quality standards and the client requirements
4. To train and develop team so as to ensure that there is an adequate supply of trained manpower in the said technology and deliver risks are mitigated
5. To gather specifications and deliver solutions to the client organization based on understanding of a domain or technology
6. To review project deliverables.
7. To recommend client value creation initiatives and implement industry best practices (on specific technology/product)
Section Title: Skill Requirements
Skill Requirements
Section Title: Must Have Skills
Must Have Skills
- Click Enter to show the proficiency description of MLOps (Machine Learning Operations)MLOps (Machine Learning Operations)
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