Senior Engineer, AVP

Stellenbeschreibung: 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 Wir streben eine Unternehmenskultur an, in der wir gemeinsam jeden Tag das Beste geben. Dazu gehören verantwortungsvolles Handeln, wirtschaftliches Denken, Initiative ergreifen und zielgerichtete Zusammenarbeit. Gemeinsam teilen und feiern wir die Erfolge unserer Mitarbeiter*innen. Gemeinsam sind wir die Deutsche Bank Gruppe. Wir begrüßen Bewerbungen von allen Menschen und fördern ein positives, faires und integratives Arbeitsumfeld. Seit über 150 Jahren wird unser Anspruch, die Globale Hausbank für unsere Kunden zu sein, von unseren Mitarbeitern vorangetrieben – in rund 60 Ländern und mit mehr als 150 Nationalitäten. Ihr tiefes Verständnis, ihre Erfahrungen, ihr Fachwissen und ihre Leidenschaft helfen unseren Kunden, sich in einer zunehmend komplexen Welt zurechtzufinden – sei es in unserer Unternehmensbank, unserer Privatkundenbank, unserer Investmentbank oder in unserem Asset Management (DWS). Gemeinsam können wir für unsere Kunden im In- und Ausland Großes bewirken und ihren dauerhaften Erfolg und ihre finanzielle Sicherheit sicherstellen. Mehr Informationen unter: Deutsche Bank Careers (db.com)