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    Job · 12871971

    HYDERABAD · FULLTIME

    Senior Agentic Full-Stack Engineers

    NTT DATA BUSINESS SOLUTIONS logo

    NTT DATA BUSINESS SOLUTIONS

    Hyderabad · onsite · Posted 61d ago

    Sourced fromNaukri
    Undisclosed7–12 yrsfulltimeHyderabad

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    Section · 01

    About this role

    Job Summary
    We are currently seeking a Senior Agentic Full-Stack Engineers to join our team in Hyderabad, Telangana, India.
    2. Senior Agentic Full-Stack Engineer
    Three openings | Agent and application engineering | End-to-end workflow implementation
    Position Details
    • Number of positions: 3
    • Level: Senior Individual Contributor
    • Primary locations: Hyderabad, Telangana, India (onshore candidates may be considered)
    • Target / alternate titles: Senior GenAI Engineer; Senior LLM Engineer; Senior AI Application Engineer; Full-Stack AI Engineer; Senior Software Engineer - Agentic AI; Applied AI Engineer
    • Core keywords: agentic AI, LLM applications, full-stack engineering, Python, Java, TypeScript, APIs, microservices, RAG, context engineering, tool calling, MCP, workflow automation, React, event-driven systems, testing, containers, Kubernetes, CI/CD, evaluation, observability
    • Recruiter red flags: Prompt-only or notebook-only experience; no production application ownership; weak API or software-engineering fundamentals; cannot work outside one language or framework; no testing, deployment, or support experience.
    Role purpose
    Build complete production-grade agentic solutions, not only the agent layer. The engineer will work from business-process understanding through implementation, integration, testing, deployment, monitoring, and continuous improvement. Each engineer must be able to develop the surrounding application and workflow components required to make an agent useful, secure, reliable, and operable.
    Client and delivery context
    Three engineers will form the main implementation capacity of the SWAT pod and may be split across parallel business-process tracks.
    The client already has platform, security, governance, and architecture capabilities; engineers are expected to use those services and focus on delivery.
    Assignments may require agent logic, conventional backend development, data processing, integration, UI development, or workflow automation depending on the use case.
    Candidates must be comfortable learning unfamiliar tools and working across languages or frameworks when that is the best fit for the client platform.
    Primary ownership
    End-to-end implementation of agents, services, workflows, retrieval, integrations, user interfaces, tests, and operational instrumentation.
    High-quality production code that follows existing enterprise security, architecture, CI/CD, and observability standards.
    Structured evaluation, debugging, performance improvement, and production support for assigned use cases.
    Reusable modules, tool patterns, and implementation documentation for broader adoption.
    Key responsibilities
    • Analyze process requirements and translate them into technical stories, interfaces, agent behaviors, workflow steps, validation rules, and acceptance criteria.
    • Build agents using appropriate patterns for tool use, planning, retrieval, state, memory, structured outputs, approvals, and exception handling.
    • Develop backend services, APIs, microservices, event handlers, data transformations, schedulers, and deterministic workflow components that support the agent.
    • Build or integrate user-facing experiences using web, chat, assistant, or embedded application patterns where required.
    • Integrate agents with enterprise systems, knowledge bases, data stores, search services, identity platforms, and approved model endpoints.
    • Implement RAG and context-engineering patterns, including ingestion, chunking, metadata, retrieval, reranking, grounding, citations, and access-aware filtering.
    • Write unit, integration, contract, security, and end-to-end tests; contribute to golden datasets, simulation, adversarial testing, and regression suites.
    • Instrument applications with logs, traces, metrics, token and cost telemetry, tool-call visibility, and user-feedback capture.
    • Deploy through existing CI/CD pipelines and support configuration, environment promotion, release validation, rollback, incident diagnosis, and remediation.
    • Participate in design and code reviews, document implementation decisions, and transfer reusable patterns to other engineers.
    Must-have candidate profile
    • 7+ years of professional software, AI/ML, platform, or application-engineering experience with strong hands-on development skills.
    • Production experience building LLM, RAG, AI assistant, agentic, intelligent workflow, or AI-enabled application capabilities.
    • Strong proficiency in Python, Java, TypeScript/Node.js, or a comparable enterprise language; willingness to work across the stack.
    • Solid knowledge of APIs, microservices, distributed systems, asynchronous processing, data structures, error handling, and automated testing.
    • Practical understanding of prompts, tool calling, structured outputs, context windows, embeddings, retrieval, state, memory, and agent failure modes.
    • Experience with containers, cloud services, CI/CD pipelines, source control, secrets, environment configuration, and application monitoring.
    • Ability to debug complex failures across model behavior, prompts, tools, data, network calls, application code, and infrastructure.
    • Clear communication, ownership mindset, and ability to deliver in a fast-moving, highly technical client environment.
    Preferred experience
    • Experience developing MCP tools or integrating with MCP servers.
    • Full-stack experience with modern web frameworks such as React, Angular, or equivalent.
    • Experience with vector databases, enterprise search, graph databases, document processing, or multimodal data.
    • Experience with one or more agent frameworks while retaining strong framework-independent engineering fundamentals.
    • Experience with model evaluation, AI tracing, prompt and tool versioning, red-team testing, and production quality gates.
    • Financial services, enterprise productivity, IT operations, identity, service management, or data-platform integration experience.
    Indicative technology exposure
    • Python, Java, TypeScript/Node.js; FastAPI, Flask, Spring Boot, Express/NestJS; React or comparable UI frameworks; LangGraph, Semantic Kernel, AutoGen, LlamaIndex, LangChain, CrewAI, or equivalent; MCP; REST/gRPC/events; SQL/NoSQL; enterprise search/vector stores; Docker/Kubernetes/serverless; Git-based CI/CD; tracing and evaluation platforms. Tool equivalence is acceptable.

    Sourced from naukri

    Section · 02

    Skills

    AutomationCI/CD PipelinesCrewaicloud servicesapisautomated testingapplication monitoringai engineerApplication EngineeringBankingAsynchronouscloudArchitectureAngularjsData ProcessingBackend DevelopmentArtificial Intelligence

    Section · Company

    About NTT DATA Business Solutions

    NTT DATA BUSINESS SOLUTIONS logo

    NTT DATA BUSINESS SOLUTIONS

    IT Services & Consulting

    4k+

    employees

    1989

    37 years old

    Hyderabad / Secunderabad, Telangana

    India

    About

    NTT DATA Business Solutions helps clients innovate and transform through expert SAP solutions, advisory, implementation, and managed services.

    Industries

    IT Services & Consulting

    Employee ratings

    2,105 reviews

    4.1/ 5

    Culture

    4.0

    Career growth

    3.5

    Work-life

    4.0

    Employees rate it well for

    Work Life Balance176Salary146Senior Management116Work Culture99Work Environment83

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