Agentic AI Engineer

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

We are currently seeking a Agentic AI Engineer to join our team in Bangalore, Karnātaka (IN-KA), India (IN).

'Job Duties : ROLE AND RESPONSIBILITIES

In this role, you will be responsible for launching and implementing GenAI agentic solutions aimed at reducing the risk and cost of managing large-scale production environments with varying complexities. You will address various production runtime challenges by developing agentic AI solutions that can diagnose, reason, and take actions in production environments to improve productivity and address issues related to production support.

What you'll do :

• . Build agentic AI systems : Design and implement tool-calling agents that combine retrieval, structured reasoning, and secure action execution (function calling, change orchestration, policy enforcement) following MCP protocol. Engineer robust guardrails for safety, compliance, and least-privilege access.
• . Productionize LLMs : Build evaluation framework for open-source and foundational LLMs implement retrieval pipelines, prompt synthesis, response validation, and self-correction loops tailored to production operations.
• . Integrate with runtime ecosystems : Connect agents to observability, incident management, and deployment systems to enable automated diagnostics, runbook execution, remediation, and post-incident summarization with full traceability.
• . Collaborate directly with users : Partner with production engineers, and application teams to translate production pain points into agentic AI roadmaps define objective functions linked to reliability, risk reduction, and cost and deliver auditable, business-aligned outcomes.
• . Safety, reliability, and governance : Build validator models, adversarial prompts, and policy checks into the stack enforce deterministic fallbacks, circuit breakers, and rollback strategies instrument continuous evaluations for usefulness, correctness, and risk.
• . Scale and performance : Optimize cost and latency via prompt engineering, context management, caching, model routing, and distillation leverage batching, streaming, and parallel tool-calls to meet stringent SLOs under real-world load.
• . Build a RAG pipeline : Curate domain-knowledge build data-quality validation framework establish feedback loops and milestone framework maintain knowledge freshness.
• . Raise the bar : Drive design reviews, experiment rigor, and high-quality engineering practices mentor peers on agent architectures, evaluation methodologies, and safe deployment patterns.

Minimum Skills Required : ESSENTIAL SKILLS

5+ years of software development in one or more languages (Python, C / C++, Go, Java) strong hands-on experience building and maintaining large-scale Python applications preferred.

3+ years designing, architecting, testing, and launching production ML systems, including model deployment / serving, evaluation and monitoring, data processing pipelines, and model fine-tuning workflows.

Practical experience with Large Language Models (LLMs) : API integration, prompt engineering, fine-tuning / adaptation, and building applications using RAG and tool-using agents (vector retrieval, function calling, secure tool execution).

Understanding of different LLMs, both commercial and open source, and their capabilities (e.g., OpenAI, Gemini, Llama, Qwen, Claude).

Solid grasp of applied statistics, core ML concepts, algorithms, and data structures to deliver efficient and reliable solutions.

Strong analytical problem-solving, ownership, and urgency ability to communicate complex ideas simply and collaborate effectively across global teams with a focus on measurable business impact.

Preferred : Proficiency building and operating on cloud infrastructure (ideally AWS), including containerized services (ECS / EKS), serverless (Lambda), data services (S3, DynamoDB, Redshift), orchestration (Step Functions), model serving (SageMaker), and infra-as-code (Terraform / CloudFormation).'

About NTT DATA

NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D.

Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client's needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees. NTT DATA recruiters will never ask for payment or banking information and will only use @nttdata.com and @talent.nttdataservices.com email addresses. If you are requested to provide payment or disclose banking information, please submit a contact us form, .

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Skills Required

Java, C, Go, Api Integration, Python