ull Stack Developer (UI + Backend), GCP & AI, AVP

📍 Job Overview

Job Title: Full Stack Developer (UI + Backend), GCP & AI, AVP

Company: Deutsche Bank

Location: Bangalore, India

Job Type: Full time

Category: Technology & Engineering Operations (Full Stack Development, Cloud Engineering, AI Implementation)

Date Posted: 2026-09-02

Experience Level: Mid-Senior Level (Equivalent to AVP)

Remote Status: On-site

🚀 Role Summary

• Develop and deliver end-to-end full-stack solutions encompassing both UI and backend services for critical transaction monitoring and data control systems.

• Design, build, and operationalize scalable, cloud-native applications leveraging Google Cloud Platform (GCP) services and modern microservices architecture.

• Implement Agentic AI and LLM-based solutions, including RAG patterns, to enhance operational efficiency, improve controls, and drive intelligent decision-making.

• Ensure application performance, resiliency, fault tolerance, observability, and security best practices are integrated throughout the development lifecycle.

• Collaborate effectively with global, cross-functional teams, including Cloud Platform, Security, Data, Risk, and Compliance, to deliver robust enterprise-grade solutions.

📝 Enhancement Note: The "AVP" designation suggests a mid-to-senior level role within Deutsche Bank, implying a need for demonstrated experience in designing and implementing complex solutions, mentoring junior developers, and contributing to architectural decisions. The focus on "Transaction Monitoring and Data Controls" within a financial institution highlights the critical nature of the work and the importance of robust, secure, and compliant systems.

📈 Primary Responsibilities

• Architect, develop, and deploy full-stack applications, ensuring seamless integration between frontend user interfaces and backend microservices.

• Create responsive, reusable, and accessible front-end components using React or Angular, adhering to modern UI/UX principles and best practices.

• Engineer robust Java-based microservices and RESTful APIs using Spring Boot, optimized for performance and scalability.

• Design and implement event-driven architectures and data processing pipelines utilizing technologies like Kafka and Apache Spark for real-time data ingestion and transformation.

• Develop and manage cloud-native applications on GCP, specifically utilizing services such as App Engine, Google Kubernetes Engine (GKE), and Cloud Run.

• Integrate AI/ML models and Agentic AI frameworks (e.g., LangChain, CrewAI) into applications, focusing on RAG patterns for enhanced contextual understanding and automated workflows.

• Drive the implementation of observability, monitoring, and alerting mechanisms to ensure high availability and proactive issue resolution.

• Champion code quality, reusability, and adherence to engineering standards across globally distributed development teams.

• Collaborate with stakeholders across various departments to gather requirements, provide technical guidance, and ensure alignment with business objectives.

• Contribute to the continuous improvement of development processes, tooling, and methodologies within the Technology, Data and Innovation (TDI) organization.

📝 Enhancement Note: The responsibilities clearly indicate a need for a developer who can own features end-to-end. The emphasis on "Agentic AI solutions," "LLM/Agentic AI and RAG-based automation," and "Agentic AI frameworks (LangChain, Google ADK, CrewAI)" points to a forward-looking role that requires hands-on experience with cutting-edge AI technologies, moving beyond traditional application development.

🎓 Skills & Qualifications

Education: While not explicitly stated, a Bachelor's or Master's degree in Computer Science, Engineering, or a related field is typically expected for an AVP-level role in a financial institution.

Experience: 5-10 years of hands-on experience in full-stack software development, with a significant portion focused on backend Java development and modern frontend frameworks.

Required Skills:

• Backend Development:

  • Proficient in Java (versions 8, 11, 17+) and the Spring Boot framework.
  • Strong experience in designing and implementing RESTful APIs and microservices architecture.
  • Experience with transactional databases (e.g., Oracle, PostgreSQL, MySQL).
  • Familiarity with event-driven architectures and message queues like Kafka.

• Frontend/UI Development:

  • Expertise in modern JavaScript frameworks such as React or Angular.
  • Strong command of TypeScript/JavaScript, HTML5, and CSS3.
  • Experience with responsive design principles and component-based architecture.
  • Proven ability to integrate frontend applications with backend services.

• Cloud & DevOps:

  • Practical experience with Google Cloud Platform (GCP) services (App Engine, GKE, Cloud Run).
  • Understanding of CI/CD principles and experience with tools like TeamCity, Jenkins, or GitHub Actions.

• AI/ML:

  • Practical experience in LLM-based application development and Agentic AI frameworks (LangChain, Google ADK, CrewAI).
  • Understanding and application of Retrieval-Augmented Generation (RAG) patterns.

• General:

  • Strong analytical and problem-solving skills with a focus on performance tuning and resilience engineering.

  • Excellent verbal and written communication skills, with experience collaborating in global teams. Preferred Qualifications:

• Experience with Red Hat OpenShift.

• Proficiency in Kotlin.

• Security implementation experience (OAuth2/OIDC).

• Frontend testing frameworks (Jest, Cypress, Playwright).

• Experience with large-scale data integration projects.

• Data engineering experience, including data partitioning and optimization for retrieval/insert performance.

• Experience handling confidential data and implementing privacy-preserving design.

• Domain experience in financial services, such as payment screening, fraud detection, or integrity monitoring.

• Familiarity with rules engines like Drools.

• Knowledge of data quality, lineage, observability, and data security principles.

📝 Enhancement Note: The required skills section is heavily populated with specific technologies. Candidates should ensure their resumes clearly highlight experience with each of these, especially Java/Spring Boot, React/Angular, GCP, Kafka, and the AI/LLM frameworks. The preferred qualifications offer significant advantages, particularly domain experience in financial services and advanced data engineering/security skills.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• End-to-End Project Examples: Showcase projects that demonstrate full-stack development capabilities, from UI design to backend implementation and cloud deployment.

• GCP Implementation Case Studies: Provide examples of applications deployed and managed on GCP services (App Engine, GKE, Cloud Run), detailing the architecture and benefits achieved.

• AI/LLM Integration Demonstrations: Include projects that illustrate the practical application of LLMs, Agentic AI, or RAG patterns to solve business problems, highlighting the impact.

• Performance & Scalability Metrics: Present quantifiable results demonstrating the performance, scalability, and resilience of systems developed, including metrics related to transaction throughput, response times, and uptime.

Process Documentation:

• Workflow Optimization: Document instances where you have analyzed and improved existing workflows or developed new, more efficient ones using technology and AI.

• System Design & Architecture: Showcase your ability to design scalable, secure, and maintainable system architectures, especially for cloud-native environments.

• CI/CD Pipeline Implementation: Provide examples of setting up and managing CI/CD pipelines for automated testing, building, and deployment of applications.

• Data Processing Pipeline Design: Illustrate your experience in designing and implementing data pipelines for ingestion, transformation, and processing using tools like Kafka and Spark.

📝 Enhancement Note: For a full-stack developer role with AI components, the portfolio should not just list projects but tell a story about the impact. Candidates should be prepared to discuss architectural decisions, trade-offs made, challenges overcome, and the quantifiable business outcomes achieved through their work, especially concerning efficiency gains from AI implementation.

💵 Compensation & Benefits

Salary Range: For an AVP-level Full Stack Developer with expertise in GCP and AI in Bangalore, India, the estimated annual salary range is typically between ₹25,00,000 to ₹45,00,000. This range can vary based on exact experience, specific skill mastery, and the candidate's negotiation.

Benefits:

• Comprehensive Leave Policy: Generous paid time off for work-life balance.

• Gender Neutral Parental Leaves: Supportive policies for new parents.

• Childcare Assistance: 100% reimbursement for childcare expenses (gender neutral).

• Professional Development: Sponsorship for industry-relevant certifications and educational programs.

• Employee Assistance Program (EAP): Confidential support services for employees and their families.

• Health Insurance: Comprehensive hospitalization coverage for employees and dependents.

• Life Insurance: Accident and Term Life Insurance policies.

• Health Screening: Complimentary health check-ups for employees aged 35 and above.

• Flexible Benefits: A customizable benefits package to suit individual needs.

Working Hours: The standard working hours are approximately 40 hours per week. While the role is on-site, Deutsche Bank often offers some flexibility within the business day to accommodate project needs and personal commitments, consistent with an AVP-level position.

📝 Enhancement Note: The salary range is estimated based on industry benchmarks for similar roles in Bangalore, considering the AVP title, the required technical skills (Java, Cloud, AI), and the financial sector. The benefits listed are extensive and align with those offered by large, established financial institutions, providing significant value beyond base compensation.

🎯 Team & Company Context

🏢 Company Culture

Industry: Financial Services (Banking)

Company Size: Deutsche Bank is a global leader in financial services, employing over 90,000 people worldwide. This large scale means opportunities for broad impact and exposure to complex, enterprise-level challenges.

Founded: 1870, indicating a long history and established presence in the global financial market.

Team Structure:

• Technology, Data and Innovation (TDI): This role is part of the TDI organization, suggesting a focus on modernizing technology, leveraging data effectively, and driving innovation.

• Transaction Monitoring and Data Controls Domain: The specific domain implies a close working relationship with compliance, risk management, and data governance teams.

• Global Collaboration: The role explicitly mentions collaborating with globally distributed teams, indicating a diverse and international working environment.

Methodology:

• Agile Delivery: The strategy emphasizes agile methodologies for efficient and iterative development.

• Cloud Modernization: A core focus is on migrating and building applications in cloud-native environments, particularly GCP.

• AI-Driven Automation: The team is actively seeking to implement AI and Agentic AI solutions to enhance operational efficiency and controls.

• Engineering Excellence: A strong emphasis is placed on building high-quality, scalable, and secure software solutions.

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

📝 Enhancement Note: Working within a large financial institution like Deutsche Bank means adhering to stringent regulatory requirements and security protocols. The TDI organization's focus on innovation and AI suggests a dynamic environment within a traditionally conservative industry, offering a unique blend of stability and forward-thinking development.

📈 Career & Growth Analysis

Operations Career Level: This role is classified as an Assistant Vice President (AVP), indicating a mid-to-senior level position. It signifies a developer who is expected to contribute significantly to solution design, implementation, and potentially guide junior team members. The scope involves end-to-end ownership of features and a strong contribution to architectural decisions.

Reporting Structure: While not explicitly detailed, an AVP typically reports to a Director or Senior Vice President within the technology division. They would likely be part of a larger team focused on specific product areas or domains within TDI. Collaboration with product owners, project managers, and other engineering leads is expected.

Operations Impact: The role has a direct impact on the bank's operational integrity and compliance. By building robust transaction monitoring and data control systems, this position helps mitigate financial risks, prevent fraud, and ensure regulatory adherence. The integration of AI/LLM solutions aims to significantly boost efficiency and effectiveness in these critical areas, contributing to cost savings and improved decision-making.

Growth Opportunities:

• Technical Specialization: Deepen expertise in advanced areas like GCP, AI/ML, event-driven architectures, or specific financial domain technologies.

• Leadership Development: Progress towards technical leadership roles, such as Tech Lead or Architect, potentially managing small teams or leading complex projects.

• Cross-functional Exposure: Gain experience working with various business units, risk, compliance, and data governance teams, broadening understanding of the financial services landscape.

• AI/ML Advancement: Become a subject matter expert in applying Generative AI and Agentic AI within the financial sector, a rapidly growing and high-demand field.

• Global Mobility: Opportunities to work with international teams and potentially contribute to projects across different Deutsche Bank locations.

📝 Enhancement Note: The AVP title implies a path towards more senior technical or management roles. The emphasis on AI and GCP provides a strong foundation for future career growth in high-demand technology areas within the financial industry. Candidates should express interest in continuous learning and taking on increasing responsibility.

🌐 Work Environment

Office Type: The job is listed as "On-site" in Bangalore, indicating a traditional office-based work environment within Deutsche Bank's facilities at Velankani Tech Park. This typically means working from a dedicated desk in an open-plan or shared office space.

Office Location(s):

• Bangalore, Velankani Tech Park, India: This is a well-established IT hub in Bangalore, likely offering good infrastructure and connectivity.

Workspace Context:

• Collaborative Environment: As part of a global team, the workspace will likely foster collaboration through team meetings, pair programming, and cross-functional discussions, both in-person and virtually.

• Technology & Tools: Access to standard corporate IT infrastructure, development tools, and potentially specialized hardware or software for AI development. The role demands proficiency with modern development tools and cloud platforms.

• Team Interaction: Opportunities for regular interaction with fellow developers, architects, product managers, and stakeholders within the TDI organization and related departments.

Work Schedule: The role is full-time, with standard working hours focused on delivering projects. While on-site, there might be some flexibility within the workday, but adherence to team schedules and project deadlines is paramount. Occasional work outside standard hours may be required for critical deployments or issue resolution.

📝 Enhancement Note: For an on-site role at a major financial institution, expect a professional and structured work environment. While collaboration is key, the specific setup (open-plan vs. cubicles) can vary. Candidates should be prepared for a typical corporate office setting in a major tech park.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: HR or recruiter call to assess basic qualifications, experience, and cultural fit.

• Technical Assessment: Online coding challenges or a take-home assignment focusing on full-stack development, Java, and potentially AI concepts.

• Technical Interviews (Multiple Rounds):

  • In-depth discussions on backend development (Java, Spring Boot, microservices, databases).
  • Frontend development assessment (React/Angular, TypeScript, UI principles).
  • Cloud computing (GCP services, architecture).
  • AI/LLM/RAG concepts and practical application.
  • Problem-solving and system design scenarios.

• Hiring Manager Interview: Focus on career aspirations, leadership potential, team fit, and strategic thinking.

• Final Round (AVP Level): May involve senior leadership or architects to assess strategic alignment and broader impact.

Portfolio Review Tips:

• Curate Select Projects: Choose 3-4 impactful projects that best showcase your full-stack, GCP, and AI capabilities.

• Quantify Achievements: For each project, clearly articulate the problem, your solution, the technologies used, and the measurable business impact (e.g., efficiency gains from AI, performance improvements, cost savings).

• Highlight AI Integration: Specifically detail how you implemented LLMs, Agentic AI, or RAG. Explain the rationale behind your choices and the challenges faced.

• Demonstrate GCP Proficiency: Showcase applications deployed on GKE, Cloud Run, or App Engine, explaining architectural decisions and benefits.

• Prepare for Deep Dives: Be ready to discuss technical details, architectural choices, trade-offs, and lessons learned for each project.

Challenge Preparation:

• System Design: Practice designing scalable, resilient, and secure systems for complex scenarios, incorporating cloud-native principles and AI components.

• Coding Proficiency: Brush up on Java, data structures, algorithms, and frontend development best practices.

• AI/LLM Concepts: Review core LLM concepts, RAG patterns, and popular frameworks like LangChain. Understand how to apply them to business problems.

• GCP Services: Familiarize yourself with key GCP services relevant to application development and deployment.

• Behavioral Questions: Prepare examples demonstrating problem-solving, collaboration, initiative, and handling of challenging situations, aligning with Deutsche Bank's values.

📝 Enhancement Note: The interview process is likely rigorous, reflecting the AVP level and the specialized skills required. Candidates should be prepared to demonstrate not just technical proficiency but also strategic thinking and a strong understanding of AI's practical application in a financial context. A well-prepared portfolio is crucial for showcasing this depth.

🛠 Tools & Technology Stack

Primary Tools:

• Backend Languages/Frameworks: Java (8/11/17+), Spring Boot

• Frontend Frameworks: React, Angular, TypeScript, JavaScript

• Cloud Platform: Google Cloud Platform (GCP) - App Engine, GKE (Google Kubernetes Engine), Cloud Run

• Messaging/Event Streaming: Kafka

• Data Processing: Apache Spark

• Databases: Oracle, BigQuery, other transactional databases

• AI/ML Frameworks: LangChain, Google ADK, CrewAI, RAG patterns

• API Development: RESTful APIs

Analytics & Reporting:

• Cloud Monitoring: GCP's native monitoring tools, potentially integrating with external APM solutions.

• Data Warehousing/Analysis: BigQuery for data storage and analysis.

• Observability Tools: Tools for logging, tracing, and metrics (e.g., Prometheus, Grafana, ELK stack - though not explicitly mentioned, common in cloud-native environments).

CRM & Automation:

• CI/CD Tools: TeamCity, Jenkins, GitHub Actions.

• Container Orchestration: Kubernetes (via GKE).

• Security Protocols: OAuth2, OIDC.

📝 Enhancement Note: The technology stack is modern and comprehensive, covering the full spectrum from backend and frontend development to cloud infrastructure and cutting-edge AI. Candidates should be adept at integrating these various components seamlessly. Experience with Kubernetes (via GKE) is essential for cloud-native development.

👥 Team Culture & Values

Operations Values:

• Engineering Excellence: A commitment to building high-quality, robust, and maintainable software solutions. This translates to a culture of code reviews, testing, and adherence to best practices.

• Innovation & AI Adoption: Embracing new technologies, particularly AI and Agentic AI, to drive efficiency and transform business processes. This encourages experimentation and a forward-thinking mindset.

• Collaboration & Global Mindset: Working effectively across diverse, globally distributed teams, valuing open communication and shared responsibility.

• Responsibility & Ethics: A strong emphasis on acting responsibly, particularly concerning data security, privacy, and the ethical use of AI in a regulated financial environment.

• Agile & Efficient Delivery: A focus on iterative development, quick feedback loops, and delivering value incrementally through agile methodologies.

Collaboration Style:

• Cross-functional Integration: Close collaboration with Cloud Platform, Security, Data, Risk, and Compliance teams is essential to ensure solutions meet enterprise standards.

• Open Communication: Encouraging open dialogue, knowledge sharing, and constructive feedback within the development team and with stakeholders.

• Process Improvement Culture: A proactive approach to identifying and implementing improvements in development workflows, tooling, and methodologies.

• Shared Ownership: Fostering a sense of collective responsibility for the success of projects and the quality of the delivered solutions.

📝 Enhancement Note: Deutsche Bank's stated values emphasize acting responsibly, thinking commercially, taking initiative, and working collaboratively. For operations and technology roles, this translates to a culture that balances innovation with rigorous control, efficiency with security, and individual contribution with team success.

⚡ Challenges & Growth Opportunities

Challenges:

• Complexity of Financial Regulations: Navigating and adhering to stringent financial regulations (e.g., for transaction monitoring) while implementing innovative solutions.

• Integration with Legacy Systems: Potentially integrating modern cloud-native and AI-driven applications with existing, older enterprise systems.

• Data Security & Privacy: Ensuring the highest levels of data security and privacy when handling sensitive financial data, especially when incorporating AI models.

• Rapid Evolution of AI: Keeping pace with the fast-changing landscape of AI technologies and effectively applying them to solve specific business problems.

• Global Team Coordination: Managing effective communication and collaboration across different time zones and cultural backgrounds.

Learning & Development Opportunities:

• Advanced GCP Training: Deepen expertise in specific GCP services relevant to scalable application development and data processing.

• AI/ML Specialization: Access to training and resources for cutting-edge AI technologies, including prompt engineering, LLM fine-tuning, and Agentic AI development.

• Financial Domain Knowledge: Opportunities to learn about various aspects of banking operations, risk management, and compliance.

• Mentorship Programs: Benefit from guidance and mentorship from senior engineers and architects within Deutsche Bank.

• Industry Conferences & Certifications: Support for attending relevant tech conferences and pursuing professional certifications in cloud, AI, or development.

📝 Enhancement Note: This role offers a unique opportunity to work at the intersection of finance, cloud technology, and artificial intelligence. The challenges are significant but come with substantial rewards in terms of professional development and impact. Candidates should be proactive learners eager to tackle complex, real-world problems.

💡 Interview Preparation

Strategy Questions:

• Scenario-Based: "Describe a complex full-stack application you designed and built. What were the key architectural decisions, trade-offs, and challenges, particularly regarding scalability and security?"

• AI Application: "How would you leverage LLMs and RAG to improve the efficiency of transaction monitoring? What are the potential risks and how would you mitigate them?"

• GCP Deployment: "Walk me through the process of deploying a microservice application on GKE. What considerations are important for production readiness?"

• Problem Solving: "Imagine a scenario where transaction monitoring alerts are generating too many false positives. How would you approach diagnosing and resolving this issue, potentially using AI?"

Company & Culture Questions:

• Motivation: "Why are you interested in working for Deutsche Bank, specifically within the Technology, Data and Innovation organization?"

• Teamwork: "Describe a time you collaborated with a global team. What strategies did you use to ensure effective communication and project success?"

• Values Alignment: "How do you ensure the responsible and ethical use of data and AI in your work?"

• Adaptability: "The AI landscape is constantly changing. How do you stay current with new technologies and apply them to your work?"

Portfolio Presentation Strategy:

• Structure: For each project, clearly present: 1. The Business Problem, 2. Your Solution (Architecture & Technologies), 3. Key Features (especially AI/GCP aspects), 4. Measurable Outcomes/Impact, 5. Lessons Learned.

• Quantify Impact: Use numbers and metrics wherever possible (e.g., "Reduced processing time by X%", "Improved accuracy of Y by Z%", "Handled X TPS").

• Technical Depth: Be prepared to dive deep into the technical implementation details, design patterns, and specific GCP services used.

• AI Rationale: Clearly articulate why AI was chosen, the specific models/frameworks used, and the value it brought. For RAG, explain the data sources and retrieval mechanisms.

• Engage and Discuss: Treat the portfolio review as a conversation, inviting questions and actively discussing your contributions and decision-making process.

📝 Enhancement Note: Interviews will likely assess not just technical skills but also the ability to think critically, solve problems creatively, and align with Deutsche Bank's values of responsibility and innovation. Demonstrating a strong understanding of how AI can be practically and ethically applied in a regulated financial environment will be key.

📌 Application Steps

To apply for this operations position:

• Submit your application: Navigate to the Deutsche Bank careers portal and submit your resume and any requested information through the provided link.

• Tailor your Resume: Ensure your resume clearly highlights your experience with Java, Spring Boot, React/Angular, TypeScript, GCP services (App Engine, GKE, Cloud Run), Kafka, Apache Spark, and especially your practical experience with LLM/Agentic AI development and RAG patterns. Use keywords from the job description.

• Prepare Your Portfolio: Curate 3-4 key projects that best demonstrate your full-stack capabilities, GCP deployments, and AI/LLM integrations. Be ready to discuss the business problem, your solution, technical details, and quantifiable impact.

• Practice Interview Questions: Rehearse answers to common technical, behavioral, and system design questions. Focus on articulating your thought process, problem-solving approach, and how you align with Deutsche Bank's values. Prepare specific examples for AI application and ethical considerations.

• Research Deutsche Bank: Understand the company's mission, values, and recent technological initiatives, particularly in areas like AI and cloud adoption. This will help you tailor your responses and demonstrate genuine interest.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.