AIOps Engineer, NCT

Deutsche Bank is hiring an AIOps Engineer, NCT in Pune, India. Level rates it ; you can apply on Deutsche Bank.

Level's read on this job

Uses AI ●●○○ is how Level rates this role: an ordinary role that requires AI tools.
The posting mentions Vertex AI, RAG and MLOps among its tools and skills.
Deutsche Bank has 1,100+ other open roles on Level.
Posted in the last few days.

AI in this role

vertex-ai

ragml-opsai-safety

Job Description:

Job Title: AIOps Engineer, NCT

Location: Pune, India

Corporate Title: NCT

Role Description

Deutsche Bank’s Strategy & Innovation Engineering team is part of the TDI Chief Strategy & Innovation Office. The team partners with business and CIO teams to evaluate emerging technologies, build and operate reusable AI capabilities, and enable safe, responsible AI adoption across the bank.
As an AIOps Engineer within the India engineering and operations team, you will develop automation and improve the reliability, observability and operational readiness of enterprise AI platforms, shared AI services and agent-based solutions. This hands-on Associate role combines cloud engineering, DevOps/MLOps and production support with AI-assisted incident analysis and controlled remediation. You will collaborate with application, platform, architecture, security and governance teams to turn operational challenges into reusable engineering solutions.

What we’ll offer you

As part of our flexible scheme, here are just some of the benefits that you’ll enjoy

Best in class leave policy
Gender neutral parental leaves
100% reimbursement under childcare assistance benefit (gender neutral)
Sponsorship for Industry relevant certifications and education
Employee Assistance Program for you and your family members
Comprehensive Hospitalization Insurance for you and your dependents
Accident and Term life Insurance
Complementary Health screening for 35 yrs. and above

Your key responsibilities

Build and maintain reusable AIOps capabilities for telemetry collection, alert correlation, incident context enrichment, root-cause analysis and operational automation.
Engineer and support cloud-native AI services on Google Cloud Platform, using GKE, Cloud Run, Vertex AI, storage, messaging and approved enterprise integrations within agreed ownership boundaries.
Develop CI/CD pipelines and reusable infrastructure-as-code modules using GitHub Actions, Terraform and container tooling, with testing, security checks and controlled releases.
Implement logs, metrics, traces, dashboards, health checks and service-level indicators to improve service visibility and reduce alert noise.
Develop AI-assisted diagnostic and runbook workflows, integrating operational knowledge and incident history; evaluate output accuracy and retain human review for consequential decisions.
Implement policy-bound remediation through approved pipelines, with least-privilege identities, approval gates, rollback, failure safeguards and traceable action records.
Contribute to production incident investigation and engineering fixes; enable L1/L2 support through runbooks, diagnostic guidance, knowledge transfer and clear escalation paths.
Improve production readiness through capacity and performance analysis, recovery testing, monitoring, support handovers and release/change documentation.
Embed applicable security, data protection and AI controls into engineering workflows; support vulnerability remediation and maintain evidence with designated control owners.
Automate onboarding, service-management integration and routine operational tasks; measure improvements in detection and resolution time, manual effort, service reliability and cost.
Document reusable patterns and contribute to proofs of concept, technical reviews and continuous improvement with global engineering and support teams.

Your skills and experience

Hands-on experience in cloud engineering, DevOps, SRE, MLOps or production engineering, with practical ownership of automation and troubleshooting tasks.
Practical Google Cloud Platform knowledge, including GKE/Kubernetes, Cloud Run, IAM, VPC networking, Cloud Storage, Cloud Logging and Cloud Monitoring.
Experience with Terraform, Git, GitHub Actions or equivalent CI/CD tooling, Docker and secure software delivery practices.
Strong Python programming skills, with working knowledge of shell scripting, SQL, REST APIs and Linux troubleshooting.
Experience implementing observability, analysing logs and metrics, investigating incidents and creating operational dashboards and runbooks.
Working knowledge of AI/ML and Generative AI applications, including model APIs, prompt and inference patterns, retrieval-augmented generation, agent workflows and evaluation.
Understanding of least privilege, workload identity, secrets management, network security, vulnerability management and auditable change practices.
Understanding of responsible AI, data protection, traceability and human oversight, with the ability to translate control requirements into practical engineering actions.
Strong analytical and problem-solving skills, clear written and verbal communication, and effective collaboration across distributed technical and control teams.

Preferred experience and qualifications: Experience with Vertex AI, OpenTelemetry, ServiceNow integrations, agent frameworks, model/agent evaluation or controlled remediation is an advantage. A bachelor’s or master’s degree in computer science, engineering or an equivalent discipline is desirable. Relevant Google Cloud, Kubernetes, DevOps/SRE or AI/ML certifications and experience in banking or another regulated industry are advantageous.

Proven ability to leverage AI tools to enhance productivity, optimise workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputs.

How we’ll support you

Training and development to help you excel in your career
Coaching and support from experts in your team
A culture of continuous learning to aid progression
A range of flexible benefits that you can tailor to suit your needs

About us and our teams

Please visit our company website for further information:

https://www.db.com/company/company.html

We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively.

Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group.

We welcome applications from all people and promote a positive, fair and inclusive work environment.

How we rate this

AIOps Engineer, NCT at Deutsche Bank rates 41 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.

Classification

Uses AI. An ordinary role that requires AI tools.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

AIOps Engineer, NCT is an open job at Deutsche Bank.
Level rates this role AI Level 2 of 4: Uses AI.
The role is based in Pune - Business Bay.
The job was posted on November 2, 2026.
Applications are handled by Deutsche Bank. Apply on Deutsche Bank

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGML OpsAI SafetyVertex AI

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How do you monitor a model once it's live, and how do you know it needs retraining?
How do you think about the risk of an AI system in this kind of role failing silently?
What's a project where you used Vertex AI hands-on?
This role expects you to use AI tools as part of the job. Which ones have you used, and for what?

Adapt your resume

List these exact terms on your resume: RAG, ML Ops, AI Safety, and Vertex AI. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Put the AI tool in a bullet point about what you did, not just in a skills list. This role treats it as a required part of the job.

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