Sr. Agentic AI/Automation Engineer | Gurugram

DigitalXNode; Gurugram District; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

DigitalXNode in India is seeking a Senior Agentic AI / Automation Engineer to design, develop, and deploy AI-powered enterprise applications using LLMs and agentic frameworks. You will collaborate with software engineers, AI researchers, cloud architects, and stakeholders to build scalable automation solutions.

Responsibilities include building autonomous AI agents, implementing RAG pipelines, and ensuring governance, security, and production-grade reliability across cloud-native platforms.

Qualifications

• Experience designing and deploying AI-powered enterprise apps using LLMs and agentic frameworks.
• Strong understanding of prompt engineering, RAG, and AI governance.
• Experience building secure RESTful APIs and integrating with enterprise data pipelines.

Responsibilities

• Design, develop, and deploy enterprise AI applications using Large Language Models (LLMs).
• Build autonomous AI agents capable of planning, reasoning, and executing multi-step workflows.
• Implement Agentic AI architectures using modern orchestration frameworks.
• Develop AI-powered automation solutions that integrate with enterprise applications.
• Build reusable AI services supporting enterprise-scale automation initiatives.
• Design AI workflows with human-in-the-loop decision-making capabilities.

Skills

LLMs

Agentic AI

RAG pipelines

Workflow orchestration

Cloud platforms

Kubernetes

Docker

Vector databases

REST APIs

Security & governance

Tools

GCP

Azure

Kubernetes

Docker

Job description

• Google Vertex AI (Preferred)
• Latency Monitoring
• Open Source AI Contributions

We are seeking an experienced Senior Agentic AI / Automation Engineer to design, develop, and deploy next-generation AI-powered enterprise applications using Large Language Models (LLMs), Agentic AI frameworks, Retrieval-Augmented Generation (RAG), workflow orchestration, and intelligent automation technologies. This role is ideal for professionals passionate about building autonomous AI agents, enterprise AI platforms, cloud-native applications, and scalable automation solutions. As a Senior Agentic AI / Automation Engineer, you will collaborate with software engineers, AI researchers, cloud architects, product managers, and enterprise stakeholders to build secure, production-grade AI systems. You will lead the development of AI-driven applications using modern foundation models, cloud platforms, vector databases, and enterprise APIs while ensuring scalability, governance, compliance, and operational excellence. This opportunity provides hands-on exposure to Generative AI, Agentic AI, LLM Engineering, AI Workflow Automation, Cloud Infrastructure, Enterprise Integration, and AI Governance, enabling you to work on cutting-edge enterprise AI transformation initiatives. Key Responsibilities Agentic AI & Generative AI Development Design, develop, and deploy enterprise AI applications using Large Language Models (LLMs). Build autonomous AI agents capable of planning, reasoning, and executing multi-step workflows. Implement Agentic AI architectures using modern orchestration frameworks. Develop AI-powered automation solutions that integrate with enterprise applications. Build reusable AI services supporting enterprise-scale automation initiatives. Design AI workflows with human-in-the-loop decision-making capabilities. LLM Engineering & AI Workflows Develop applications using OpenAI, Anthropic Claude, Google Gemini, or similar foundation models. Implement Prompt Engineering techniques to improve model accuracy and reliability. Design Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge systems. Build structured prompting and tool-calling workflows. Fine-tune AI models where appropriate to improve business outcomes. Optimize AI reasoning, response quality, and inference performance. Enterprise AI Integration Integrate AI services with enterprise APIs, internal applications, and business platforms. Develop secure RESTful APIs supporting AI-powered applications. Connect AI systems with enterprise data pipelines and knowledge repositories. Build scalable backend services supporting AI inference and automation. Enable AI-driven business process automation across enterprise systems. Cloud & Platform Engineering Deploy AI workloads on Google Cloud Platform (GCP), Microsoft Azure, or Kubernetes environments. Develop cloud-native AI applications using Docker and Kubernetes. Manage scalable AI infrastructure supporting enterprise workloads. Optimize cloud resource utilization and operational efficiency. Implement secure deployment strategies following enterprise cloud standards. Vector Databases & Knowledge Retrieval Design enterprise Retrieval-Augmented Generation (RAG) architectures. Integrate vector databases such as Pinecone, Weaviate, Elasticsearch, or OpenSearch. Build semantic search and enterprise knowledge retrieval systems. Improve AI response quality using intelligent document retrieval strategies. Optimize indexing, embeddings, and retrieval performance. AI Performance, Monitoring & Optimization Monitor AI application performance, latency, accuracy, and cost efficiency. Evaluate LLM outputs using automated evaluation frameworks. Implement AI observability and monitoring solutions. Optimize prompts, caching strategies, batching, and model selection. Detect model drift and continuously improve AI performance. Security, Governance & Responsible AI Implement Responsible AI principles throughout the AI lifecycle. Ensure compliance with enterprise security, governance, and regulatory standards. Design secure AI applications with encryption, IAM, and access control. Support AI risk assessments and governance reviews. Maintain secure AI deployment pipelines for regulated enterprise environments. Leadership & Collaboration Lead technical initiatives across enterprise AI engineering projects. Mentor engineers in AI engineering best practices and software development. Participate in architecture reviews and technical strategy discussions. Collaborate with product managers, architects, security teams, and business stakeholders. Stay updated with emerging AI technologies, frameworks, and industry best practices.