AI Engineering AIDLC And AIOps

LTM; Mumbai; On-site; INR 450,000 - 750,000; Full time

Job summary

LTM in Mumbai seeks an experienced AI Leader to drive enterprise-scale AI Development Lifecycle, AI Engineering and AI Operations with deep expertise in GenAI, ML, DL and cloud platforms. You will define standards, governance, operating models and delivery frameworks for scalable, secure and responsible AI.

Build AI platform ecosystems, drive automation, monitoring and continuous optimization, and ensure value realization across programs.

Qualifications

• Experience leading enterprise AI DLD and AI engineering programs.
• Proven ability to define standards, governance, and delivery frameworks.
• Strong knowledge of GenAI, ML, DL, and AI safety considerations.
• Experience with cloud platforms, preferably Azure.

Responsibilities

• Define enterprise AIDLC frameworks and standards.
• Lead AI platform architecture and GenAI delivery.
• Oversee AI Governance, risk, and compliance.
• Drive AI deployment and monitoring with AIOps.
• Integrate ServiceNow Orchestrator for automation.
• Measure KPIs like deployment velocity and AI ROI.

Skills

AI Architect

SDLC

Agile

GenAI

Tools

Azure Cognitive Services

Deep Learning

Reinforcement Learning

GenAI

LLMOps

MLOps

Job description

Job Description:

Role Description

AI Architect SDLC experience Agile AI savvy

Job Summary

Seeking an experienced AI Leader to drive enterprisescale AI Development Lifecycle AI Engineering and AI Operations with expertise in advanced AI technologies and cloud platforms

Job Description

Lead the organizations AI Development Lifecycle AIDLC AI Engineering practices and AI Operations AIOps across enterprise programs Define standards governance operating models and delivery frameworks for scalable secure responsible and measurable AI implementations Establish AI engineering ecosystems for rapid development deployment monitoring and continuous optimization of AI solutions Ensure compliance security reliability and business value realization in AI initiatives Drive adoption and integration of advanced AI technologies including Azure Cognitive Services Deep Learning Reinforcement Learning GenAI LLMOps and Machine Learning Lead AI platform strategy focusing on scalability performance resiliency and security Integrate ServiceNow Orchestrator to automate AI deployment and support operations Oversee AI Governance risk management and compliance aligned with ethical AI and privacy standards

Roles and Responsibilities

• Define and institutionalize enterprise AIDLC frameworks methodologies and standards
• Establish best practices for AI solution design development testing deployment and maintenance
• Drive Responsible AI and AI Governance practices
• Create reusable AI accelerators frameworks and assets
• Lead AI platform architecture and engineering teams with focus on GenAI Agentic AI ML Azure Cognitive Services and Data Science delivery models
• Define AI architecture standards and reference architectures ensuring system scalability performance resiliency and security
• Build and govern AI Operations AIOps processes including ModelOps MLOps and LLMOps frameworks
• Implement continuous monitoring model performance management and drift detection mechanisms
• Define AI incident management and operational excellence processes
• Drive automation across AI deployment and support ecosystems leveraging ServiceNow Orchestrator
• Define AI governance policies ensuring compliance with security privacy risk and ethical AI requirements
• Lead AI risk and compliance reviews
• Measure success through KPIs such as AI deployment velocity model accuracy platform availability cost optimization AI adoption rate MTTR and AI ROI realization
• Utilize expertise in Deep Learning Reinforcement Learning GenAI and AIOps to enhance AI capabilities and operational efficiency