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AI Engineering

NTT Ltd

Bengaluru

3-5 years

Today

$41.0K–60.2K/yr

Full-time

Onsite

Skills Required

LLM APIs

RAG

LangChain

Embeddings

Vector Database

Python

React

TypeScript

JavaScript

FastAPI

Flask

Pandas

Java

Spring Boot

REST API

Description

Senior AI engineering role for the DB Intelligence programme, focused on building production-grade AI-enabled applications for banking workflows. The work combines full stack engineering, AI/ML services, data integration and secure enterprise delivery.

Company: NTT DATA

Role: Senior AI Engineer / Senior Full Stack AI Engineer / AI Platform Engineer

Location: Bangalore, Karnātaka (IN-KA), India (IN)

Experience

- Significant professional software engineering experience

- Recent hands-on delivery of AI, data, analytics or decision-support platforms

- Strong React and modern front-end engineering experience

- TypeScript / JavaScript experience

- State management experience

- Reusable component design experience

- Responsive UI development experience

- Strong Python engineering experience

- Experience with FastAPI / Flask

- Experience with Pandas

- Experience with data pipelines

- Experience with AI/ML libraries

- Experience with LLM integration

- Experience with model evaluation or automation frameworks

- Strong Java engineering experience

- Experience with Spring Boot

- Experience with REST APIs

- Experience with microservices

- Experience with event-driven architectures

- Experience with resilience and enterprise integration patterns

- Experience building production-grade applications

- Understanding of security, scalability, availability, latency, observability and maintainability

- Practical GenAI / AI application experience

- Experience with LLM APIs

- Experience with prompt engineering

- Experience with embeddings

- Experience with vector databases

- Experience with RAG

- Experience with semantic search

- Experience with agent workflows

- Experience with hallucination mitigation and guardrails

- Experience integrating enterprise data sources and APIs

- Experience with SQL databases

- Experience with document stores

- Experience with search platforms

- Experience with messaging/event platforms

- Experience with data lakes

- Solid understanding of secure engineering

- Understanding of authentication/authorisation

- Understanding of entitlement models

- Understanding of data protection and audit requirements

- Experience working in Agile delivery teams

- Ability to communicate complex technical concepts to technical and non-technical stakeholders

- Financial services experience is highly valuable

- Experience in regulated banking environments

- Understanding of data sensitivity, operational resilience, model risk, access controls, evidence-based decisioning and governance expectations

Responsibilities

- Design and build AI-enabled applications for DB Intelligence

- Build user-facing workflows, APIs, microservices, orchestration components and data integration layers

- Develop modern React / TypeScript front ends with reusable components and strong API integration

- Support explainable AI-assisted workflows through front-end user experiences

- Build Python services for AI/ML integration,



model orchestration, RAG, agentic workflows, data processing, evaluation pipelines and automation

- Develop and integrate Java / Spring Boot microservices for enterprise backend capabilities, business rules, workflow orchestration and secure service-to-service communication

- Work with structured and unstructured data sources including internal systems, documents, market/event data, portfolio data and enterprise knowledge sources

- Contribute to AI architectures using LLM APIs, prompt orchestration, embeddings, vector search, RAG, model evaluation, guardrails and human-in-the-loop review

- Engineer solutions that support scenario analysis, event-driven intelligence, impact assessment, portfolio/risk insight generation and decision support

- Apply clean code, automated testing, CI/CD, code reviews, observability, performance tuning, resilience and production support readiness

- Implement controls for data privacy, entitlement management, audit logging, explainability, traceability, model output monitoring and responsible AI usage

- Provide senior technical contribution, design leadership, mentoring and reusable engineering patterns across the programme

- Work closely with product owners, data scientists, quants, risk specialists, architects, cyber/security, compliance and business stakeholders

- Deliver reliable, explainable, secure and observable solutions aligned to Deutsche Bank standards

Additional Responsibilities

- Corporate level to be validated: AVP, VP or Director depending on experience

- Programme context: strategic AI agenda focused on embedding trusted, scalable AI into business-critical banking workflows

- DB Intelligence applies AI to decision intelligence, scenario analysis and risk-aware insight generation using external developments and internal portfolio and exposure data

- Senior, hands-on engineer with strong ownership, comfort with ambiguity, pragmatic problem solving and the ability to balance innovation with control, resilience and regulatory expectations

- Collaborative and credible with senior technology, business, risk and compliance stakeholders

- Confirm programme branding, target level, location, employment model and working pattern

- Confirm preferred cloud/platform stack and any mandatory DB tooling, standards or security requirements

- Confirm whether the role should lean full stack AI, AI platform, front-end product, backend Java or Python/ML engineering

- Confirm priority banking domain experience such as risk, markets, portfolio analytics, credit, KYC or research

Nice To Have

- Cloud platforms such as Google Cloud, AWS or Azure

- Kubernetes

- Docker

- Terraform

- Helm

- CI/CD tooling such as GitHub Actions, GitLab CI or Jenkins

- Vector/search technologies such as pgvector, Elasticsearch/OpenSearch, Vertex AI Search, Pinecone, Weaviate or FAISS





- LLM frameworks/orchestration tools such as LangChain, LlamaIndex, Semantic Kernel, Haystack or equivalent

- Model evaluation for RAG/GenAI systems including factuality, grounding, citation accuracy, retrieval precision/recall, latency, toxicity, bias and robustness

- Observability tooling such as Prometheus, Grafana, OpenTelemetry, Splunk, ELK or cloud-native monitoring

- Responsible AI, model governance, AI risk management, explainability, audit trails and UX patterns for AI-assisted workflows

- Financial services experience in investment banking, corporate banking, risk, markets, research, KYC, credit, portfolio analytics or regulatory technology

More Skills

AI/ML libraries, LLM integration libraries, microservices, SQL, PostgreSQL, search platforms, cloud-native platforms, Kubernetes, Docker, CI/CD, automated testing, observability, secure SDLC tooling, prompt orchestration, model evaluation, guardrails, Google Cloud, AWS, Azure, Helm, GitHub Actions, GitLab CI, Jenkins, pgvector, Elasticsearch, OpenSearch, Vertex AI Search, Pinecone, Weaviate, FAISS, LlamaIndex, Semantic Kernel, Haystack, Prometheus, Grafana, OpenTelemetry, Splunk, ELK

Other

- NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us

- Inclusive, adaptable and forward-thinking organization

- NTT DATA is a $30 billion business and technology services leader

- Serves 75% of the Fortune Global 100

- Committed to accelerating client success and positively impacting society through responsible innovation

- Leading AI and digital infrastructure provider with capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services

- Global Top Employer with experts in more than 50 countries

- Access to a robust ecosystem of innovation centers and established and start-up partners

- Part of NTT Group, which invests over $3 billion each year in RD

- Whenever possible, local hiring to NTT DATA offices or client sites

- Many positions offer remote or hybrid work options subject to client requirements

- In-office attendance may be required for meetings or events depending on business needs

- Equal opportunity employer

- Qualified applicants receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status

Prepare for this role

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