5 days ago
Sibiu, Romania +3 moreSenior
Responsibilities
- Analyze business needs, user journeys, data constraints, risks, and non-functional requirements for AI-enabled capabilities.
- Design and build end-to-end frontend, backend, AI orchestration, data retrieval, integration, security, and operational components.
- Develop accessible user interfaces, backend services, APIs, asynchronous processes, and integration components.
- Integrate machine-learning and generative-AI services through model APIs, SDKs, hosted endpoints, and platform services.
- Implement prompt management, structured outputs, retrieval-augmented generation, embeddings, vector search, tool calling, and workflow orchestration.
- Build secure data ingestion, transformation, retrieval, persistence, authentication, authorization, and privacy controls.
- Create unit, integration, contract, end-to-end, regression, and AI-specific quality, safety, latency, groundedness, and cost evaluations.
- Implement safeguards, validation, fallback behavior, human-in-the-loop controls, graceful degradation, logging, metrics, traces, alerts, and operational signals.
- Contribute to containerization, environment configuration, release automation, production verification, rollback, and model or prompt promotion.
- Diagnose production incidents, perform root-cause analysis, document architectures and operational procedures, participate in reviews, mentor engineers, and improve engineering standards.
Requirements
- BSc or MSc in Computer Science or a related field.
- At least 8 years of software engineering experience.
- Strong full-stack experience with a modern frontend framework and a production backend stack.
- Strong knowledge of JavaScript or TypeScript and familiarity with Angular, React, Node.js, Python, Java, Spring Boot, or equivalent frameworks.
- Experience with AI assistant platforms and CLI tools, and hands-on integration of machine-learning or generative-AI capabilities into user-facing or enterprise software.
- Ability to take AI-enabled features from technical design and implementation through testing, deployment, monitoring, and support.
- Experience with integrations, data models, authentication flows, asynchronous processing, resilient distributed applications, SQL and NoSQL data stores, search technologies, caching, and data pipelines.
- Practical understanding of machine-learning and generative-AI concepts, model APIs, embeddings, retrieval-augmented generation, vector stores, AI workflow orchestration, prompt engineering, structured outputs, tool or function calling, model selection, context management, and AI response evaluation.
- Experience with automated testing, Git, CI/CD, containerization, cloud services, observability, and production support.
- Knowledge of responsible AI, privacy, security, explainability, human oversight, and risk-control principles.
- Ability to troubleshoot browser, API, application, data, model, and infrastructure layers.
- Strong communication, documentation, analytical, collaboration, and product-oriented problem-solving skills, plus professional working proficiency in English.
Tech Stack
Categories
About NTT DATA
NTT DATA is a Tokyo‑headquartered, publicly traded IT services firm within the NTT Group. It provides consulting, application development, system integration, cloud and enterprise application services, and managed/outsourcing services for large enterprises and public-sector organizations. The company operates in more than 50 countries and is listed on the Tokyo Stock Exchange.