Agentic Ai Engineer Persistent Pune Chennai Bengaluru

Vibehackers; Hinoba-an; On-site; PHP 1,658,000 - 2,653,000; Full time

Job summary

Vibehackers seeks a Lead Agentic AI Engineer to design, build, and operate agentic AI systems that integrate LLMs and GenAI frameworks to enable multi-step workflows and enterprise integrations.

You will architect cloud-native deployments on Azure, containerize services with Docker and Kubernetes, implement observability, and ensure security and performance at scale across enterprise APIs and ecosystems.

Qualifications

• Total experience: ~7 years.
• Relevant experience: ~2 years with agentic AI concepts or systems.
• Proficiency in Python and GenAI frameworks (LangChain).
• Hands-on experience with LLMs, prompts, evaluation, and API integrations.

Responsibilities

• Design and build agentic AI systems and multi-step orchestration workflows.
• Integrate and optimize LLMs, including prompting, evaluation, and performance tuning.
• Develop APIs and enterprise integrations to expose AI capabilities.
• Implement cloud-native deployments and manage Azure-based infrastructure.
• Containerize services and manage deployments with Docker and Kubernetes.
• Ensure security, scalability, and performance of AI services.
• Implement observability and monitoring for AI services.

Skills

Python

LLM integration

Prompt engineering

API development

Enterprise integration

Cloud architecture

Observability & monitoring

Tools

LangChain

Docker

Kubernetes

Azure

Job description

Agentic Ai Engineer Persistent Pune Chennai Bengaluru

Directly builds agentic AI workflows and integrates LLMs using GenAI frameworks like LangChain, so it's tightly aligned with vibe coding and AI-assisted development.

About the Role

Lead Agentic AI Engineer to design, build, and operate agentic AI systems that integrate LLMs, orchestrate multi-step workflows, and deliver scalable, secure AI services with enterprise APIs and cloud/container platforms.

Job Description

Role

Lead Agentic AI Engineer responsible for architecting, implementing, and operating agentic AI systems that integrate large language models (LLMs) and GenAI frameworks to enable multi-step workflows, orchestration, and enterprise integrations.

Key Responsibilities

• Design and build agentic AI systems and multi-step orchestration workflows.
• Integrate and optimize LLMs including prompt engineering, evaluation, and performance tuning.
• Develop APIs and enterprise integrations to expose AI capabilities.
• Implement cloud-native deployments and manage infrastructure on Azure.
• Containerize services and manage deployments with Docker and Kubernetes.
• Ensure security, scalability, and performance of AI services (non-functional requirements).
• Implement observability and monitoring for AI services to track reliability and performance.

Requirements

• Total experience: ~7 years (as indicated).
• Relevant experience: ~2 years working with agentic AI concepts or systems.
• Proficiency in Python.
• Experience with GenAI frameworks (e.g., LangChain) or similar.
• Hands-on experience integrating and optimizing LLMs (prompting, optimization, evaluation).
• Experience building APIs and integrating with enterprise systems.
• Experience with cloud platforms, specifically Azure.
• Experience with containerization and orchestration: Docker and Kubernetes.
• Knowledge of security, scalability, performance considerations for AI systems.
• Experience with observability, monitoring, and operational tooling for AI services.

Skills

LLM integration Agentic system design Prompt engineering API development Enterprise integration Cloud architecture Containerization Orchestration Security Scalability Performance optimization Observability and monitoring