Principal Agentic AI Engineer / Hands-on Technical Lead

NTT DATA, Inc.; Gurgaon; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

NTT DATA Services in India seeks a Principal Agentic AI Engineer / Hands-on Technical Lead in Hyderabad (IN-TG), India. You will own end-to-end production delivery of agentic AI solutions, guide multi-domain work streams, and contribute hands-on coding across Python, Java, and TypeScript.

The role requires deep expertise in agents, tool calls, context and memory, RAG, and cloud-native architectures, with responsibilities spanning design reviews, implementation, and knowledge transfer to teams.

Qualifications

• 10+ years of software, platform, AI/ML, or distributed-systems engineering experience, including recent hands-on coding responsibility.
• Demonstrated production delivery of LLM, RAG, agentic AI, AI assistant, workflow automation, or intelligent application solutions.
• Strong proficiency in Python, Java, or TypeScript with ability to work across the stack.
• Deep understanding of agent patterns, tool calling, context engineering, state and memory, RAG and safe fallbacks.
• Experience designing APIs, microservices, event-driven systems, data integrations, and cloud-native apps.
• Practical experience with CI/CD, containers, Kubernetes, automated testing, logging, tracing, observability, and production support.
• Ability to explain trade-offs across quality, latency, cost, security, and portability.
• Strong communication skills for client-facing technical work.

Responsibilities

• Decompose end-to-end processes with stakeholders to identify decision points and data dependencies.
• Define operating patterns for agent-based solutions and tool sets with proper oversight.
• Design and build production agents, APIs, microservices, and workflow logic.
• Review MCP server patterns, authentication, error handling, and observability.
• Guide multi-agent orchestration, model routing, state management, retries and timeouts.
• Contribute code, perform reviews, and ensure production readiness and governance alignment.

Skills

Python

Java

TypeScript

CI/CD

Kubernetes

APIs

Microservices

Cloud

Agent patterns

Observability

Tools

FastAPI

Spring Boot

LangGraph

Semantic Kernel

AutoGen

CrewAI

LlamaIndex

LangChain

MCP SDKs

REST

gRPC

Job description

Date: Aug 10, 2026

Company: NTT DATA Services

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 Principal Agentic AI Engineer / Hands-on Technical Lead to join our team in Hyderabad, Telangana (IN-TG), India (IN).

1. Principal Agentic AI Engineer / Hands-on Technical Lead

Agent applicability | Technical leadership | Hands-on engineering | Production delivery

Number of positions

1

Level

Principal Engineer / Hands-on Technical Lead

Primary locations

Hyderabad or Noida preferred; exceptional onshore candidates may be considered

Target / alternate titles

Principal AI Engineer; Staff Agentic AI Engineer; Lead GenAI Engineer; Principal LLM Engineer; Hands-on AI Solution Lead; Lead AI Application Engineer

Core keywords

agentic AI, LLM, GenAI, business-process decomposition, agent patterns, MCP, tool calling, context engineering, RAG, workflow orchestration, Python, Java, TypeScript, APIs, microservices, cloud, Kubernetes, CI/CD, evaluation, observability

Recruiter red flags

Architecture-only or advisory-only profile; no recent coding; prototype-only experience; cannot explain personal code contribution; framework evangelism; weak production troubleshooting; treats every use case as an agent.

Client and delivery context

• The client already has enterprise AI infrastructure, production MCP capabilities, security and governance controls, and delivery pipelines. The lead must plug into those capabilities and accelerate execution.
• The pod may work across multiple business domains rather than one fixed function. The lead must rapidly understand new processes and guide two or more delivery tracks when needed.
• The role must balance rapid implementation with reusable engineering patterns, operational reliability, enterprise controls, and knowledge transfer to internal teams.
• The lead should be language-, cloud-, model-, and framework-agnostic and able to work with the client's existing technology choices.

Primary ownership

• Process-to-solution assessment, including whether a requirement calls for an agent, deterministic workflow, retrieval, conventional application logic, or a hybrid pattern.
• Technical direction for agents, MCP tools, context and memory, enterprise integrations, orchestration, evaluation, observability, and production readiness.
• Hands-on contribution to critical code paths, design spikes, integration patterns, code reviews, debugging, and release readiness.
• Reusable reference implementations, engineering standards, and knowledge-transfer assets that internal teams can replicate.

Key responsibilities

• Work with business and engineering stakeholders to decompose end-to-end processes, identify decision points, data dependencies, controls, exceptions, and measurable outcomes.
• Determine where agentic AI is appropriate and define the operating pattern, autonomy boundary, tool set, context strategy, human oversight, and fallback behavior.
• Design and build production agents and supporting services, including APIs, microservices, event handlers, retrieval components, workflow logic, user-facing interfaces, and integration adapters.
• Define and review MCP server and tool patterns, tool schemas, authentication, authorization, error handling, versioning, and observability.
• Guide multi-agent and workflow orchestration, model selection or routing, state management, retries, timeouts, idempotency, queues, and exception management.
• Establish structured evaluation for task success, groundedness, tool correctness, safety, latency, cost, user acceptance, and regression prevention.
• Contribute directly to code, conduct code and design reviews, resolve complex technical issues, and help engineers move features through test and production environments.
• Align implementations with existing security, architecture, data, privacy, Responsible AI, and production-approval processes without duplicating established governance functions.
• Mentor senior engineers, split work across parallel use cases, manage technical dependencies, and maintain a high bar for engineering quality and delivery pace.
• Create reusable patterns, runbooks, implementation guidance, and technical documentation for subsequent internal scaling.

Must-have candidate profile

• 10+ years of software, platform, AI/ML, or distributed-systems engineering experience, including recent hands-on coding responsibility.
• Demonstrated production delivery of LLM, RAG, agentic AI, AI assistant, workflow automation, or intelligent application solutions.
• Strong proficiency in at least one enterprise programming language such as Python, Java, or TypeScript, with the ability to work across the broader stack as required.
• Deep understanding of agent patterns, tool calling, context engineering, state and memory, RAG, structured outputs, human-in-the-loop controls, and failure-mode design.
• Experience designing APIs, microservices, event-driven systems, data integrations, authentication patterns, and cloud-native applications.
• Practical experience with CI/CD, containers, Kubernetes or equivalent runtimes, automated testing, logging, tracing, observability, and production support.
• Ability to explain technical trade-offs across quality, latency, cost, security, portability, reliability, and implementation speed.
• Strong communication skills with the credibility to work directly with highly technical client stakeholders and senior engineers.

Preferred experience

• Experience establishing or leading an Agentic AI pod, innovation factory, engineering SWAT team, or accelerated delivery team.
• Hands-on experience developing MCP servers and tools or equivalent standardized enterprise tool-integration layers.
• Experience with model gateways, multi-model routing, policy-based model selection, private models, or provider abstraction.
• Experience in financial services, data and analytics platforms, regulated enterprises, or environments handling sensitive proprietary data.
• Experience across two or more public-cloud ecosystems and multiple commercial or open-source model providers.
• Experience transferring reusable patterns to internal engineering teams and scaling from initial use cases to a broader program.

Python, Java, TypeScript/Node.js; FastAPI, Spring Boot, or equivalent services; LangGraph, Semantic Kernel, AutoGen, CrewAI, LlamaIndex, LangChain, or equivalent agent frameworks; MCP SDKs; REST/gRPC/events; vector and enterprise search; relational and NoSQL databases; Kubernetes, containers, serverless; CI/CD; OpenTelemetry and AI tracing; commercial and open-source LLMs. Specific tools are illustrative, not mandatory.

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, https://us.nttdata.com/en/contact-us .

NTT DATA endeavors to make https://us.nttdata.com accessible to any and all users.

If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at https://us.nttdata.com/en/contact-us .

This contact information is for accommodation requests only and cannot be used to inquire about the status of applications.

NTT DATA is an equal opportunity employer.

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

For our EEO Policy Statement, please click here .

If you'd like more information on your EEO rights under the law, please click here .

For Pay Transparency information, please click here .