Uttar Pradesh Mlops technical lead Jobs – 58 Open Jobs Today

Assistant Vice President - AI Runtime Security
EXL Service —Noida, Uttar Pradesh
- Full-time
- Azure
- Computer Science
- Master's degree
Sr Administrator (Support & Operations)
HCLTech —Gautam Budh Nagar, Uttar Pradesh
- Full-time
- Azure
- AWS
- AI
7d
PE || 2025021 || Computer Vision Architect || WDTS
Droisys Inc —Unknown, Uttar Pradesh
- Azure
- Doctoral degree
- Computer Science
Quick apply
Senior Assistant Vice President- AI Security Engineering
EXL Service —Noida, Uttar Pradesh
- Full-time
- Azure
- Computer Science
- Master's degree
Java Fullstack - Lead
Iris Software —Noida, Uttar Pradesh
- Oracle
- Computer Science
- Java
- Health insurance
1d
Senior Machine Learning Engineer
Siemens —Noida, Uttar Pradesh
- Full-time
- Computer Science
- Master's degree
- AWS
Systems Integration Specialist Advisor
NTT Ltd —Noida, Uttar Pradesh
- Azure
- Master's degree
- AWS
AI/ML Architect
Luxoft —Noida, Uttar Pradesh
- Doctoral degree
- Computer Science
- System design
1d
Systems Integration Senior Specialist Advisor
NTT Ltd —Noida, Uttar Pradesh
- Full-time
- Azure
- Doctoral degree
- Computer Science
AI/ML Instructor & Program Mentor Intern
Fusionpact Career —Noida, Uttar Pradesh
- Azure
- Computer Science
- Laboratory experience
Quick apply

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Assistant Vice President - AI Runtime Security

EXL Service -
Noida, Uttar Pradesh

Apply Now

Job details

Full-time

Qualifications

CI/CD
Azure
Law
Computer Science
Git
Master's degree
Bachelor's degree
NIST standards
Continuous integration
GitHub
APIs
Data science
AI
RMF
Jenkins

Full job description

Job Description: Strong runtime protection for AI systems in production
Reduced exposure to AI misuse, data leakage, and agent abuse
Clear alignment to NIST AI RMF, security-by-design, and regulatory runtime expectations
Defensible governance posture for clients, auditors, and regulators

Responsibilities: Define and own enterprise AI governance controls focused on runtime security, monitoring, and enforcement for GenAI, LLM, RAG, and Agentic AI systems in production.
Establish technical standards for runtime threat detection and prevention, covering prompt injection, agent manipulation, inference abuse, data leakage, hallucination exploitation, and unauthorized model access.
Ensure AI runtime architectures incorporate guardrails, policy enforcement points, and telemetry collection across APIs, orchestration layers, model gateways, and inference pipelines.
Oversee implementation of continuous monitoring and observability mechanisms, including behavioral monitoring, data and concept drift detection, usage anomalies, and output risk indicators.
Institutionalize governance requirements for runtime risk response, including alerting thresholds, automated containment, escalation workflows, and integration with enterprise cyber and incident response processes.
Partner with platform, security, and MLOps/LLMOps teams to embed runtime controls into CI/CD pipelines, model deployment workflows, and API management layers without impacting delivery velocity.
Define governance expectations for secure AI operation at scale, including access control, rate limiting, logging, explainability at runtime, and auditable control evidence.
Lead technical governance for high‑risk and regulated AI deployments, ensuring runtime behavior complies with internal policies, client contractual commitments, and global regulatory expectations (e.g., NIST AI RMF).
Act as the technical advisor for AI runtime risk decisions, advising executive stakeholders and clients on production readiness, risk acceptance, and control effectiveness.

Qualifications: Bachelor’s or Master’s degree in Computer Science, Information/Cyber Security, AI/ML, Data Science, or related field

10-15+ years overall experience, including 3+ years in AI governance, AI runtime threat vectors and AI observability, monitoring, and drift management

Proven ability to design and govern runtime guardrails using AI governance and risk platforms (e.g., Credo.ai for AI inventory, policy enforcement, and risk assessment)

Strong hands‑on understanding of runtime monitoring and observability for AI systems, leveraging LLMOps/MLOps platforms such as MLflow, Weights & Biases, Datadog, Azure Monitor, CloudWatch, or equivalent, to track usage patterns, behavioral anomalies, and model drift in production.

Command of drift detection and AI behavior monitoring, including data drift, concept drift, and output instability, using observability and model monitoring tools (e.g., Aporia, Datatron, custom telemetry built on OpenTelemetry).

Ability to operationalize AI runtime governance controls within CI/CD and deployment pipelines, embedding security checks and enforcement into MLOps/LLMOps workflows orchestrated through platforms such as Kubeflow, Airflow, GitHub Actions, Azure DevOps, or Jenkins.

Apply Now

Refine Your Search

mlops technical lead jobs in uttar pradesh

Assistant Vice President - AI Runtime Security

Sr Administrator (Support & Operations)

PE || 2025021 || Computer Vision Architect || WDTS

Senior Assistant Vice President- AI Security Engineering

Java Fullstack - Lead

Senior Machine Learning Engineer

Systems Integration Specialist Advisor

AI/ML Architect

Systems Integration Senior Specialist Advisor

AI/ML Instructor & Program Mentor Intern

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