Home/Jobs/AI Engineering 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

Strong 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, cutting-edge 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 Recommended resources to build the skills for this position. Sponsored. Python for Everybody Specialization Coursera Learn Python from scratch — variables, data structures, web scraping, and databases.

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