Senior Engineer, AVP

Posted 13 Days Ago
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Magarpatta, Hadapsar, Pune, Maharashtra, IND
In-Office
Senior level
Fintech • Financial Services
The Role
Develops and deploys AI/ML systems, agentic workflows, and scalable batch and real-time ETL pipelines. Builds intelligent AI agents, integrates MLOps and DataOps practices, creates CI/CD and infrastructure-as-code solutions, and supports model and pipeline troubleshooting. Responsibilities include testing deterministic and generative AI outputs, optimizing performance and cost, implementing architectural changes, managing releases, and documenting AI and data systems. The role also mentors junior team members and collaborates across the software and data lifecycle.
Summary Generated by Built In
Job Description:

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.

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

  • 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.

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 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.

Skills Required

  • Bachelor of Science degree in Computer Science, Data Science, AI, Software Engineering, or equivalent, with a minor in Finance, Mathematics, or Engineering
  • Strong analytical and problem-solving skills involving unstructured data, big data processing, and complex decision trees
  • Proficient communication skills for explaining AI, machine learning, and big data engineering concepts to nontechnical stakeholders
  • Fluent English communication skills, written and verbal
  • Ability to work in virtual teams and matrixed organizations
  • Strong Python and PySpark development skills
  • Hands-on experience with Apache Spark, Hadoop, and robust ETL/ELT pipelines for large-scale datasets
  • Knowledge of GCP AI/ML and data services, including Vertex AI, BigQuery, Dataproc, Dataflow, Agent Builder, and Document AI
  • Knowledge of Gemini, LangChain, LlamaIndex, AI frameworks for multi-agent systems, and retrieval-augmented generation pipelines
  • Knowledge of machine learning and deep learning concepts, supervised and unsupervised learning, model fine-tuning, and evaluation metrics
  • Knowledge of Terraform and workflow orchestration tools such as Apache Airflow or Vertex AI Pipelines
  • Understanding of financial services compliance, risk guidelines, AI governance, and data privacy
  • Ability to work in a fast-paced environment with competing priorities and maintain delivery focus
  • Experience with MLOps and DataOps practices, including model registries, feature stores, model monitoring, and data quality frameworks
  • Knowledge of vector databases
  • Knowledge of HP ALM, Jira, ServiceNow, SDLC, and Agile processes

Deutsche Bank Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Deutsche Bank and has not been reviewed or approved by Deutsche Bank.

  • Healthcare Strength — Health coverage is positioned as comprehensive, spanning multiple medical plan options along with dental, vision, prescription coverage, life insurance, and disability protection.
  • Leave & Time Off Breadth — Time away is described as generous, including annual leave, sick leave, public holidays, wellbeing leave, volunteering leave in some regions, and expanded bereavement leave in certain locations.
  • Retirement Support — Retirement support is presented as a matched savings plan (401(k)), reinforcing longer-term financial security as part of the rewards package.

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The Company
HQ: Frankfurt am Main
68,787 Employees

What We Do

At Deutsche Bank, we give original thinkers the space and support they need to shine. Merging local knowledge with global vision, in-depth insight with industry-leading digital expertise, if you’re an innovator by nature, we can help you to unleash your potential. We see things differently at Deutsche Bank – and we’re proud of our fresh perspective. Today, we’re driving growth through our strong client franchise, investing heavily in digital technologies, prioritising long-term success over short term gains, and serving society with ambition and integrity. Wherever your interests lie – in investment banking, trading, private wealth, asset management, retail banking - or many of the infrastructure functions that support them – you’ll discover resources, training and opportunities designed to keep you ahead of the curve. Intelligence has no boundaries: we welcome high-achieving, talented individuals from any background. If you’re full of imagination, enjoy solving problems and respond positively to complex challenges, discover a career to look forward to and join us!

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