Job Title: TWIN AI Engineer

Department: Production STA – AIOPS

About Business line/Function: The BNP Paribas Group's IT department (IT GROUP) aims to ensure the overall consistency of the Information System (IS) with the Group's strategic objectives, while improving the management and control of operational risks.  

The role of IT includes, among other things, providing enhanced customer experience, accelerating digitalization, and optimizing operational efficiency. Thus, IT GROUP has modernized the Information Systems by deploying digital levers to support the digitalization of the Group's Businesses and Functions:  

• The delivery of digital levers (Cloud, API, Data, Digital Working, Tech watch) is effective, and the IT Market Place enables their deployment on a Group-wide scale,  
• The security of the IT environment is evolving with a focus on cybersecurity risks and IT resilience to meet increasingly stringent regulatory requirements,  
• The robustness of the Information Systems is improving with the implementation of standardized operational methods,  
• Human capital remains at the center of our priorities,  
• Operational efficiency is growing with a focus on process automation and industrialization,  
• All these advances contribute to the Group's ambition to reduce its environmental footprint. 

Thanks to these solid foundations, a new phase of the IT strategy is opening up, enabling the Group to address a dual challenge: accelerating the adoption of innovative solutions around data and Artificial Intelligence (AI), and ensuring the interoperability and security of Information Systems.  

To meet these challenges, IT GROUP is adapting its organization and remaining in line with that of the Bank. This evolution is based on five main levers:  

• Technological innovation through data and AI: ensuring excellence in innovation through research and development of skills, relying on specific governance. This involves structuring technical foundations to the state of the art in order to accelerate experimentation, the construction of innovative solutions, and their adoption on a large scale by the Business and Functions,  
• Cybersecurity: continuing to protect the Bank and its customers in terms of Cybersecurity and Cyber Fraud, in line with regulatory requirements,  
• Infrastructure and Production: creating synergies, accelerating industrialization, emphasizing interoperability, and improving the resilience of Information Systems, while controlling risks,  
• Payment and Card Services: meeting the challenges of the industry by ensuring optimal alignment and end-to-end execution of strategic programs among all Group stakeholders,  
• Operational excellence: gaining efficiency, particularly in financial terms, to continue optimizing expenses.

Position Purpose: 

AIOPS

The Twin Knowledge Engineering Specialist will build and maintain the knowledge pipelines that allow Twin agents to produce reliable, explainable and grounded answers.

The role will contribute to:

• ingestion of operational knowledge; 
• metadata enrichment; 
• semantic structuring; 
• RAG and GraphRAG preparation; 
• knowledge graph population; 
• knowledge quality controls; 
• source traceability; 
• certification of exposed sources; 
• detection of obsolete, duplicated or contradictory knowledge; 
• continuous improvement of knowledge retrieval. 

The key principle is:

No reliable Twin without reliable knowledge engineering.

Responsibilities

Direct Responsibilities

1. Engineer knowledge ingestion pipelines

Build and operate the technical pipelines used to ingest knowledge into Twin.

Responsibilities include:

·         Implement ingestion workflows for documents, procedures, FAQs, incident knowledge, change knowledge, infrastructure knowledge and operational standards. 

·         Extract content from structured and unstructured sources. 

·         Normalize formats before ingestion. 

·         Apply metadata enrichment. 

·         Manage document versioning and lifecycle metadata. 

·         Prepare content for RAG indexing. 

·         Prepare content for graph-based representation when relevant. 

·         Detect ingestion errors, incomplete documents and unsupported formats. 

·         Implement automated quality checks before exposure to Twin agents. 

2. Structure knowledge for RAG and GraphRAG

Transform raw knowledge into AI-usable knowledge.

Responsibilities include:

·         Define and apply chunking strategies. 

·         Implement semantic tagging. 

·         Add metadata such as owner, source system, validity date, confidentiality level, domain, franchise, CI, application, service and operational scope. 

·         Optimize retrieval quality through indexing strategy. 

·         Support hybrid search, semantic search and graph-assisted retrieval. 

·         Link knowledge chunks to entities in the knowledge graph. 

·         Maintain relationships between applications, infrastructure components, procedures, incidents, changes and services. 

·         Improve grounding and source citation capabilities. 

3. Build and maintain knowledge graph content

Support the creation and maintenance of graph-based knowledge used by Twin.

Responsibilities include:

·         Model key IT production entities and relationships. 

·         Populate graph structures from documentation, CMDB, inventories and operational sources. 

·         Support entity resolution and deduplication. 

·         Detect inconsistent relationships. 

·         Contribute to graph quality checks. 

·         Support GraphRAG use cases. 

·         Validate graph traversal results used by agents. 

·         Work with Twin Core and graph specialists on ontology, schema and graph evolution. 

4. Implement knowledge quality controls

Develop controls to ensure that Twin consumes trusted and usable knowledge.

Responsibilities include:

·         Implement automated checks for missing metadata. 

·         Detect obsolete documents. 

·         Detect duplicated or conflicting content. 

·         Flag documents without owner or validation date. 

·         Track source freshness. 

·         Monitor knowledge coverage by domain or franchise. 

·         Detect knowledge pollution or drift. 

·         Implement rules to prevent unvalidated content from being exposed to critical agents. 

·         Produce quality reports for knowledge owners and Twin franchises. 

5. Support source certification and exposure rules

Engineer the technical mechanisms that control which knowledge sources can be used by Twin agents.

Responsibilities include:

·         Maintain a technical registry of knowledge sources. 

·         Track source certification status. 

·         Implement exposure rules by agent, franchise, domain and confidentiality level. 

·         Ensure traceability between generated answers and source knowledge. 

·         Support access control and data protection requirements. 

·         Implement source usage monitoring. 

·         Ensure that critical answers can be linked back to validated sources. 

·         Support auditability of knowledge consumption. 

6. Improve retrieval and answer grounding

Continuously improve the ability of Twin agents to retrieve the right knowledge and produce grounded answers.

Responsibilities include:

·         Analyze failed retrieval cases. 

·         Identify missing, poorly structured or wrongly indexed knowledge. 

·         Improve chunking and metadata strategies. 

·         Tune search and retrieval parameters. 

·         Build test datasets for RAG / GraphRAG evaluation. 

·         Compare expected sources versus retrieved sources. 

·         Support evaluation of answer grounding, contextualization and explainability. 

·         Work with AI Response Review teams to identify knowledge-related failures. 

Supervised technologies:

·         Understanding of agentic architecture.

·         Expertise RAG / GraphRAG.

·         Data & Quality Governance.

·         Intercultural communication.

·         Leadership and knowledge of the BNP context.

Contributing Responsibilities

Key Technical Deliverables

• Knowledge ingestion pipelines; 
• RAG-ready content datasets; 
• GraphRAG-ready knowledge structures; 
• knowledge metadata model; 
• chunking and tagging standards; 
• source certification registry; 
• knowledge quality dashboards; 
• automated quality control scripts; 
• knowledge graph entity and relationship mappings; 
• retrieval evaluation datasets; 
• source traceability reports; 
• knowledge refresh monitoring; 
• obsolete / duplicate / contradictory content detection reports. 

Technical & Behavioral Competencies

AI and Agentic Engineering

·         Practical understanding of LLM-based applications. 

·         Experience with prompt engineering. 

·         Understanding of agent workflows and agent orchestration. 

·         Knowledge of RAG-based support systems. 

·         Ability to evaluate answer quality and failure modes. 

·         Understanding of hallucination, grounding, context retrieval and escalation logic. 

Support Automation

·         Experience with ITSM tools such as ServiceNow, Jira or equivalent. 

·         Experience designing support workflows. 

·         Knowledge of ticket classification, routing and prioritization. 

·         Ability to automate repetitive support actions. 

·         Understanding of L1 / L2 / L3 support models, but from an engineering perspective. 

Data and Analytics

·         Ability to structure feedback data. 

·         Experience with dashboards and operational KPIs. 

·         Ability to detect patterns in user complaints. 

·         Basic data analysis skills. 

·         Understanding of classification, clustering and tagging mechanisms. 

Integration Skills

·         API integration experience. 

·         Experience connecting support workflows with ITSM, backlog or knowledge platforms. 

·         Understanding of event-driven or workflow-based automation. 

·         Ability to work with engineering teams on integration patterns. 

Specific Qualifications: 

10  - 12 years of experience.

Skills Referential (Required knowledge, skills and abilities)

Technical Skills:

·         Understanding of agentic architecture.

·         Expertise RAG / GraphRAG.

·         Data & Quality Governance.

·         Intercultural communication.

·         Leadership and knowledge of the BNP context.

Behavioral Skills: 

o    Excellent Communications

o    Ability to collaborate / Teamwork

o    Ability to understand, explain & support change

o    Attention to detail / rigor

Education Level: Graduate & Above

Location: Mumbai (MH)

About BNP Paribas Group:

BNP Paribas is the European Union’s leading bank and key player in international banking. It operates in 65 countries and has nearly 185,000 employees, including more than 145,000 in Europe. The Group has key positions in its three main fields of activity: Commercial, Personal Banking & Services for the Group’s commercial & personal banking and several specialized businesses including BNP Paribas Personal Finance and Arval; Investment & Protection Services for savings, investment, and protection solutions; and Corporate & Institutional Banking, focused on corporate and institutional clients. Based on its strong diversified and integrated model, the Group helps all its clients (individuals, community associations, entrepreneurs, SMEs, corporates and institutional clients) to realize their projects through solutions spanning financing, investment, savings and protection insurance. In Europe, BNP Paribas has four domestic markets: Belgium, France, Italy, and Luxembourg. The Group is rolling out its integrated commercial & personal banking model across several Mediterranean countries, Turkey, and Eastern Europe. As a key player in international banking, the Group has leading platforms and business lines in Europe, a strong presence in the Americas as well as a solid and fast-growing business in Asia-Pacific. BNP Paribas has implemented a Corporate Social Responsibility approach in all its activities, enabling it to contribute to the construction of a sustainable future, while ensuring the Group's performance and stability.

About BNP Paribas India Solutions:

Established in 2005, BNP Paribas India Solutions is a wholly owned subsidiary of BNP Paribas SA, European Union’s leading bank with an international reach. With delivery centers located in Bengaluru, Chennai and Mumbai, we are a 24x7 global delivery center. India Solutions services three business lines: Corporate and Institutional Banking, Investment Solutions and Retail Banking for BNP Paribas across the Group. Driving innovation and growth, we are harnessing the potential of over 10000 employees, to provide support and develop best-in-class solutions.

Commitment to Diversity and Inclusion

At BNP Paribas, we passionately embrace diversity and are committed to fostering an inclusive workplace where all employees are valued, respected and can bring their authentic selves to work. We prohibit Discrimination and Harassment of any kind and our policies promote equal employment opportunity for all employees and applicants, irrespective of, but not limited to their gender, gender identity, sex, sexual orientation, ethnicity, race, colour, national origin, age, religion, social status, mental or physical disabilities, veteran status etc. As a global Bank, we truly believe that inclusion and diversity of our teams is key to our success in serving our clients and the communities we operate in. As a global Bank, we truly believe that inclusion and diversity of our teams is key to our success in serving our clients and the communities we operate in.