At a glanceSummarised by Seekless from the posting.
Must have16
6-10 years of IT experience as a hands-on engineer
Deep proficiency in Python
Advanced SQL including complex query optimization and data modelling
Extensive hands-on experience building solutions on GCP
Mastery of BigQuery
Mastery of Cloud Composer (or Apache Airflow)
Mastery of Cloud Run
Proficient in defining infrastructure as code using Terraform
Designing and managing robust CI/CD pipelines using Cloud Build, Artifact Registry
Strong understanding of modern data patterns, distributed systems, and architectural best practices
Hands-on experience designing and developing conversational AI solutions using Dialogflow CX or CX Agent Studio
Extensive hands-on experience building enterprise AI solutions using Gemini Enterprise Agent Platform
Proven experience building and deploying production-grade RAG systems
Deep understanding of LLMs, vector databases, and embedding models
Strong practical experience designing and developing agentic AI applications and workflows using Google Agent Development Kit (ADK)
Demonstrable experience in operationalizing AI models and hosting applications using Docker
Skills
Python
SQL
GCP
BigQuery
Cloud Composer
Cloud Run
Terraform
Cloud Build
Artifact Registry
Gemini Enterprise Agent Platform
Dialogflow CX
CX Agent Studio
Google Agent Development Kit (ADK)
Docker
REST APIs
Pub/Sub
Benefits
Gender neutral parental leaves
Childcare assistance
Certification sponsorship
Employee assistance program
Health insurance
Accident insurance
Term life insurance
Health screening
Job Description:
Job Title: GCP Data & AI Engineer, AS
Location: Pune, India
Role Description:
As an AVP and Senior GCP Data and AI Engineer, you will lead the architecture and hands-on delivery of complex data and generative AI solutions on GCP. Working as a senior individual contributor, you will translate business and technical requirements into production-ready designs; build scalable batch and streaming pipelines, APIs, RAG systems, and agentic workflows; and establish engineering standards for security, testing, deployment, resilience, and operational support. You will own solutions from design through production deployment and provide technical guidance on critical engineering decisions and complex production issues.
What we’ll offer you
As part of our flexible scheme, here are just some of the benefits that you’ll enjoy
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Best in class leave policy.
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Gender neutral parental leaves
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100% reimbursement under childcare assistance benefit (gender neutral)
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Sponsorship for Industry relevant certifications and education
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Employee Assistance Program for you and your family members
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Comprehensive Hospitalization Insurance for you and your dependents
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Accident and Term life Insurance
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Complementary Health screening for 35 yrs. and above
Your key responsibilities:
As a Senior Engineer, your hands-on responsibilities will include:
AI & Application Development:
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Design, build, and operationalize sophisticated AI applications, including production-grade RAG pipelines on GCP.
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Leverage the Gemini Enterprise Agent Platform to train, fine-tune, and deploy machine learning and generative AI models.
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Design and implement complex agentic workflows to automate and optimize business processes.
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Design, develop, integrate, secure, version, test, deploy, consume, and operate mission-critical REST APIs using Python, with containerised deployment on Cloud Run.
Data Engineering & Pipelines:
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Design, develop, and maintain scalable batch and streaming data pipelines using Python, SQL, Cloud Composer, and Pub/Sub.
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Develop and optimize complex SQL queries in Big Query for large-scale data analysis, extraction, and transformation.
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Automate data quality and ETL testing procedures using Python and SQL.
Infrastructure & Operations:
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Develop and deploy all cloud infrastructure as code using Terraform.
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Implement and manage CI/CD pipelines for data and AI applications, including automated testing, security checks, controlled environment promotion, and reliable production deployment.
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Own security and governance controls for data and AI solutions, including IAM, least-privilege access, encryption, secrets management, audit logging, data protection, and compliance with enterprise standards.
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Serve as a key escalation point for complex L3 production issues, providing expert troubleshooting and resolution.
Your skills and experience
Mandatory Engineering Skills:
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6-10 years of IT experience as a hands-on engineer, including responsibility for designing, building, deploying, and supporting large-scale data systems in production.
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Expert-Level Languages: Deep proficiency in Python and advanced SQL, including complex query optimization and data modelling.
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Cloud Platform: Extensive hands-on experience building solutions on GCP. Experience with Azure or AWS is also valuable.
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Core GCP Services: Mastery of Big Query, Cloud Composer (or Apache Airflow), and Cloud Run in production environments.
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Infrastructure & Automation: Proficient in defining infrastructure as code using Terraform and designing and managing robust CI/CD pipelines using Cloud Build, Artifact Registry, automated testing, vulnerability scanning, and environment-based release strategies.
Advanced Technical & Design Expertise: We expect candidates to have deep, practical experience in the following areas, with a portfolio of projects demonstrating their expertise.
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System Design: Strong understanding of modern data patterns, distributed systems, and architectural best practices.
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Conversational AI: Hands-on experience designing and developing conversational AI solutions and chatbots using Dialog flow CX (Conversational Agents) or CX Agent Studio.
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Gemini Enterprise Agent Platform: Extensive hands-on experience building enterprise AI solutions using the Gemini Enterprise Agent Platform, including agent configuration, integration, evaluation, security, deployment, and operational monitoring.
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Generative AI Systems: Proven experience building and deploying production-grade RAG (Retrieval-Augmented Generation) systems. Deep understanding of LLMs (like Gemini), vector databases, and embedding models.
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Agentic AI Application & Workflow Development: Strong practical experience designing and developing agentic AI applications, complex workflows, agentic patterns, and multi-agent systems using the Google Agent Development Kit (ADK). Knowledge of concepts such as the A2A (agent-to-agent) protocol and agent cards is highly desirable.
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AgentOps & Application Hosting: Demonstrable experience in operationalizing AI models and hosting applications using containers (Docker).
How we’ll support you
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Training and development to help you excel in your career
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Coaching and support from experts in your team
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A culture of continuous learning to aid progression
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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.