AI Requirements Engineer - Senior Engineer, AVP

Job Title: AI Requirements Engineer-Senior Engineer, AVP

Location: Pune, India

Role Description

• The Deutsche India is seeking a talented AI Requirement Engineer to join our growing team. At the “Service Solutions and AI” Domain, our mission is to revolutionize our Private Bank process landscape by implementing holistic, front-to-back process automation. As a Private Bank AI Centre of Excellence, we are responsible for strategy building and execution of AI innovation, governance, and delivery across Private Bank, ensuring standardization, compliance, and accelerated adoption of AI solutions. We are dedicated to leveraging the power of data and AI to drive innovation, optimize operations, and deliver exceptional value to our customers. We are committed to enhancing efficiency, agility, and innovation, with a keen focus on aligning every step of our process with the customer’s needs and expectations. Our dedication extends to driving innovative technologies, such as AI & workflow services, to foster continuous improvement. We aim to deliver “best in class” solutions across products, channels, brands, and regions, thereby transforming the way we serve our customers and setting new benchmarks in the industry.
• Join our innovative team as an AI Requirement Engineer, where you will be instrumental in bridging the gap between business requirements and AI technical solutions. You will play a pivotal role in understanding, analyzing, and translating complex business needs into functional specifications for AI-powered applications. This role requires a strong analytical mindset, excellent communication skills, and a solid understanding of both business processes and AI capabilities to drive effective and impactful AI implementations.

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

Strategic Business & AI Opportunity Identification:

• Process Analysis & Problem Framing: Collaborate extensively with senior business stakeholders to deeply understand current processes, identify critical pain points, and strategically pinpoint opportunities where AI can deliver significant business value and efficiencies.
• AI Value Proposition: Lead the assessment of potential AI impact and articulate clear value propositions for proposed AI solutions.

Requirements Leadership & Documentation:

• Elicitation & Analysis: Lead the elicitation, comprehensive analysis, and meticulous documentation of detailed functional and non-functional requirements for complex AI solutions, ensuring clarity, conciseness, and strict alignment with overarching business objectives.
• Traceability Management: Ensure robust traceability of requirements throughout the entire AI project lifecycle, typically utilizing tools like Jira and Confluence.

AI Solution Design & Prototyping:

• Technical Concept Translation: Work closely with AI Engineers and Data Scientists to translate intricate business requirements into precise technical concepts and contribute significantly to the architectural design of AI solutions.
• UI/UX Contribution: Provide valuable input on UI/UX aspects for AI applications, ensuring user-centric design.

Stakeholder Engagement & Management:

• Liaison & Facilitation: Act as the primary liaison and facilitator between diverse business units and highly technical teams, driving effective communication, proactively managing expectations, and ensuring seamless alignment throughout the AI project lifecycle.
• Conflict Resolution: Utilize strong negotiation and conflict resolution skills to manage differing viewpoints and drive consensus among various teams and stakeholders.

Data Analysis & AI Suitability:

• Data Readiness Assessment: Analyze existing data sources and critically assess data quality to determine their suitability and readiness for AI applications.
• Data Collaboration: Collaborate effectively with data engineering and data science teams to ensure optimal data preparation and governance for AI initiatives.

AI Use Case Definition & Prioritization:

• Use Case Strategy: Define clear and impactful AI use cases, rigorously assess their potential business impact, and lead the prioritization of AI initiatives based on strategic value, feasibility, and alignment with organizational goals.

User Acceptance Testing (UAT) & Validation:

• UAT Leadership: Facilitate, manage, and support User Acceptance Testing (UAT) for AI solutions, ensuring that deployed systems rigorously meet defined business requirements and exceed user expectations.

Performance Monitoring & Optimization:

• Success Metrics Definition: Contribute significantly to defining key metrics for AI solution success, monitor their performance post-deployment, and proactively identify areas for continuous improvement and optimization.

Regulatory Compliance & Ethical AI:

• Compliance Assurance: Ensure that all AI solutions strictly adhere to relevant regulatory requirements and ethical guidelines.
• Bias & Risk Mitigation: Proactively identify and lead efforts to mitigate potential biases, risks, and fairness concerns associated with AI deployment.

Change Management & Adoption:

• Adoption Strategy: Support and lead change management activities to facilitate the successful adoption of new AI tools and processes within the business, maximizing user engagement and value realization.

Market Research & Innovation Trends:

• Emerging Technology Monitoring: Continuously stay informed about emerging AI technologies, market trends, and industry best practices.
• Strategic Insights: Proactively identify new opportunities and provide strategic insights to inform and shape future AI initiatives and decisions.

Your skills and experience

Educational Foundation:

• Academic Background: Bachelor’s or Master’s degree in Business Administration, Information Technology, Computer Science, or a related quantitative field.

Professional Expertise:

• Extensive Business Analysis Experience: Proven experience (8+ years) as a Business Analyst, Functional Analyst, or similar role, with a demonstrated leadership focus on technology projects, ideally within AI/ML domains.

Core Business Analysis Competencies:

• Business Analysis Leadership: Strong proficiency and leadership in business process modeling, advanced requirements gathering, and comprehensive documentation techniques.

Analytical & Problem-Solving Acumen:

• Critical Thinking: Excellent analytical and critical-thinking abilities to deeply understand complex business problems and effectively translate them into actionable, innovative AI solutions.

Communication & Presentation Leadership:

• Executive Communication: Exceptional verbal and written communication skills, with the ability to articulate complex technical concepts clearly to non-technical stakeholders and present strategic findings persuasively to diverse audiences.

AI/ML Familiarity & Application:

• AI/ML Foundational Understanding: Foundational understanding of AI and Machine Learning concepts, including Large Language Models (LLM), Natural Language Processing (NLP), and their potential business applications.

Data Understanding & Quality:

• Data Analysis & Suitability: Strong familiarity with data analysis, data quality concepts, and the ability to work with complex data to identify patterns and insights.

Stakeholder Management & Influence:

• Strategic Stakeholder Engagement: Proven ability to effectively engage with, influence, and manage diverse stakeholders across business and technical teams at all levels.

Tools & Methodologies Proficiency:

• Business Analysis Tools: Proficiency with leading business analysis tools (e.g., Jira, Confluence, Visio).
• Data Visualization Tools: Familiarity with data visualization tools (e.g., Tableau, Power BI) for presenting insights.
• SQL: Basic understanding of SQL for data extraction and analysis is a significant plus.
• Agile Expertise: Extensive experience with Agile methodologies and frameworks.

​Domain Knowledge (Highly Preferred):

• Financial Services Domain: In-depth experience in the financial services industry, particularly Private Banking, is highly desirable.

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.