Senior Engineer, AVP

Deutsche Bank AG; Pune District; Presencial; INR 2.500.000 - 3.500.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Leave policy

Parental leave

Childcare reimbursement

Sponsorship for certifications

Employee Assistance Program

Hospitalization insurance

Life insurance

Health screening

Descripción de la vacante

Deutsche Bank AG in Pune, India, seeks a Senior Engineer, AVP to design, develop, and deploy high-performance data pipelines, AI/ML features, and cognitive solutions. You will contribute to Enterprise AI, data engineering, and multi-agent systems, ensuring secure, maintainable deployments and scalable ETL/ELT workflows.

The role emphasizes collaboration in SDLC, MLOps, and DataOps while mentoring juniors. Strong Python/PySpark skills, GCP Vertex AI, and domain knowledge in financial services are

Formación

• Bachelor of Science degree in Computer Science, Data Science, AI, or Software Engineering (with a minor in Finance, Mathematics, or Engineering).
• Strong analytical and problem-solving skills for unstructured data and big data processing.
• Excellent communication to explain AI/ML and data engineering concepts to non-technical stakeholders.
• Fluent in English (written/verbal).
• Ability to work in virtual teams and matrixed organizations.

Responsabilidades

• Designs, develops, and delivers AI/ML and ETL/ELT pipelines for large-scale datasets.
• Develops and deploys AI infrastructure components (Python, PySpark, Vertex AI, Agentic frameworks).
• Builds Intelligent AI Agents for planning, tool-use, and multi-agent collaboration.
• Debugs and supports deployed AI/ML models and data pipelines (L3).
• Ensures code quality with peer reviews and testing for deterministic ETL and non-deterministic AI outputs.
• Implements CI/CD for AI models and data pipelines on target environments.

Conocimientos

Python

PySpark

GCP Vertex AI

Agentic AI

Data engineering

ML models

Big Data

Airflow

Terraform

LangChain

Educación

BSc in CS/DS/AI/SE

Herramientas

Jira

ServiceNow

HP ALM

GitHub Copilot

Vertex AI Pipelines

Descripción del empleo

Job Title: Senior Engineer, AVP Location: Pune, India

Role Description

A Senior Engineer is responsible for designing, developing, and delivering robust high-performance data pipelines, intelligent agentic workflows, Machine Learning Models, and cognitive solutions to solve complex business problems and accomplish organizational goals. Key responsibilities of this role include active participation in the design, development, and deployment of artificial intelligence (AI), machine learning (ML), Agentic AI, and enterprise data engineering features. This includes investigating re-use, ensuring that AI Agent/ML and ETL solutions are fit for purpose, secure, and maintainable, and ensuring they can be integrated successfully into the overall enterprise environment with clear, robust, and well-tested deployment pipelines. Assists more junior members of the team and controls their work where applicable.

• Develops and deploys source code, including infrastructure and application-related configurations for AI/ML, Agentic AI, and large-scale data processing components, in accordance with software requirement specifications.
• Provides Development activities for Projects, ETL pipelines, and AI infrastructure components (i.e., Python, PySpark, GCP Vertex AI, Agentic frameworks, Machine Learning pipelines, and Infrastructure as a Code).
• Designs and builds Intelligent AI Agents capable of planning, tool-use, multi-agent collaboration, and executing complex reasoning tasks.
• Designs, develops, and maintains scalable Batch and Real-time ETL/ELT pipelines to ingest, clean, and transform massive structured and unstructured datasets.
• Debugs, fixes, and provides support to the L3 support team for deployed AI/ML models, data pipelines, and applications.
• Verifies developed source code, data transformation logic, and prompt configurations by peer reviews (4-eyes principle).
• Contributes to quality assurance by writing and conducting unit, integration, and evaluation testing specifically designed for both deterministic ETL pipelines and non-deterministic AI outputs (e.g., LLM evaluations).
• Ensures architectural changes (as defined by Enterprise/AI/Data Architects) are implemented.
• Contributes to problem and root cause analysis for cognitive pipelines, data pipeline bottlenecks, and ML model drift or performance degradation.
• Integrates software components following the integration strategy, MLOps, and DataOps guidelines.
• Works on technical continuous improvements across AI/ML and data modules regularly (e.g., query performance tuning, PySpark job optimization, latency optimization, context window management, cost reduction).
• Where applicable, develops CI/CD routines to deploy AI models, data pipelines, and agentic workflows to target environments.
• Provides Release Deployments on non-Production Management controlled environments.
• Supports creation of Software Product Training Materials, Software Product User Guides, and Software Product Deployment Instructions for AI and data systems.
• Collaborates with colleagues participating in other stages of the Software Development Lifecycle (SDLC), MLOps, and Data Lifecycle.

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 skills and experience

General Skills

• Bachelor of Science degree from an accredited college or university with a concentration in Computer Science, Data Science, AI, or Software Engineering (or equivalent) – with a minor in Finance, Mathematics, or Engineering.
• Strong analytical and problem-solving skills, specifically in handling unstructured data, big data processing, and complex decision trees.
• Proficient communication skills with the ability to explain complex AI/ML and Big Data engineering concepts to non-technical stakeholders.
• Fluent in English (written/verbal).
• Ability to work in virtual teams and in matrixed organizations.
• Excellent team player and open-minded.
• Keeps pace with rapid technical innovation in Generative AI, Large Language Models (LLMs), Agentic architectures, and Big Data technologies.
• Understands the relevant business area and relevant Financial Services compliance/risk guidelines around AI and data privacy.
• Ability to share information, transfer knowledge, and expertise to team members.
• Ability to work in a fast-paced environment with competing and alternating priorities with a constant focus on delivery.

Domain Specific Skills

Very Good knowledge of the following technologies and concepts is required: Programming: Strong Python and PySpark development skills. Big Data & ETL: Hands‑on experience with Apache Spark, Hadoop, and designing robust ETL/ELT pipelines for processing large‑scale datasets. Cloud Platform: GCP (Google Cloud Platform) AI/ML and Data services (Vertex AI, BigQuery, Dataproc, Dataflow, Agent Builder, Document AI). Agentic AI & GenAI Frameworks: Gemini, Github Copilot, LangChain, LlamaIndex, AI frameworks for building multi‑agent systems and RAG (Retrieval‑Augmented Generation) pipelines. Machine Learning: Core ML/DL concepts, supervised/unsupervised learning, model fine‑tuning, and evaluation metrics. Automation & Orchestration: Infrastructure as Code (Terraform) and Workflow orchestrators (Apache Airflow or Vertex AI Pipelines). Good to have: Experience with MLOps and DataOps practices (Model Registry, Feature Store, Model Monitoring, Data Quality frameworks). Knowledge of Vector Databases Very good Knowledge about core processes / tools such as HP ALM, Jira, ServiceNow, SDLC, and Agile processes. 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 more 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. For over 150 years, our dedication to being the Global Hausbank for our clients has been driven by our people – in around 60 countries and across more than 150 nationalities. Their deep understanding, insights, expertise, and passion help our clients navigate an increasingly complex world – be it in our Corporate Bank, our Private Bank, our Investment Bank or our Asset Management (DWS) division. Together we can make a great impact for our clients at home and abroad, securing their lasting success and financial security. More information at: Deutsche Bank Careers (db.com)