AI Engineer – Agentic AI & Automation

About the Role

Job Description: AI Engineer – Agentic AI \& Automation **Experience:** 5–8 Years **Employment Type:** Full\-Time **Role:** AI Engineer / Senior AI Engineer **Work Mode:** On\-site **Department:** Engineering / AI \& Automation **Applications Submitted Through this link will only be accepted:** https://careers.osseducation.com/POS\-011 **About the Role** We are looking for an experienced **AI Engineer** with 5–8 years of software engineering experience and strong hands\-on expertise in **AI automation, Agentic AI, LLM\-based applications, browser automation, MCP servers, and AI developer tooling**. The ideal candidate should be capable of designing and implementing intelligent automation systems using tools such as **Claude, OpenAI Codex, n8n, Selenium, Playwright, MCP (Model Context Protocol), Hooks, AI Agents, and Sub\-Agents**. This role requires someone who understands not only how to use AI tools, but also how to **architect, integrate, optimize, monitor, and productionize AI\-powered engineering workflows**. Key Responsibilities1\. Agentic AI \& AI Engineering * Design and develop **Agentic AI systems** capable of autonomous task execution, decision\-making, tool usage, and workflow orchestration. * Build AI Agents and **Sub\-Agent architectures** for complex multi\-step tasks. * Design agent workflows involving: * Planning * Reasoning * Tool execution * Context management * Task delegation * Validation * Error handling * Human\-in\-the\-loop approval * Develop reusable AI agents for software development, testing, data processing, business automation, and operational workflows. * Evaluate different LLMs and AI models based on **quality, latency, reliability, and token/cost consumption**. 2\. Claude \& Codex Engineering Workflows * Hands\-on experience with **Claude / Claude Code** and **OpenAI Codex**. * Build AI\-assisted software development workflows using coding agents. * Understand and optimize: * Context window usage * Input/output token consumption * Cached tokens * Context reuse * Prompt efficiency * Agent execution cost * Model selection * Analyze AI coding\-agent usage and identify opportunities to reduce unnecessary token consumption. * Design workflows that intelligently decide when to use: * Main Agent * Sub\-Agent * Lightweight model * High\-reasoning model * Cached context * External tools * Experience with AI coding\-agent workflows involving repository analysis, impact analysis, code generation, testing, debugging, and deployment. 3\. MCP Server Development \& Integration * Strong understanding of **Model Context Protocol (MCP)**. * Develop, configure, and integrate MCP servers with AI agents and coding assistants. * Build custom MCP tools to expose: * APIs * Databases * Internal systems * File systems * Git repositories * CI/CD systems * Business applications * Design secure tool\-access patterns and permission boundaries for AI agents. * Integrate MCP servers with Claude, Codex, and other AI\-enabled development environments. * Troubleshoot MCP tool invocation, authentication, context, and integration issues. 4\. Hooks \& AI Developer Automation * Implement and maintain **AI coding\-agent Hooks** for automated engineering workflows. * Use hooks for activities such as: * Pre\-processing * Post\-processing * Code validation * Formatting * Security checks * Testing * Git operations * Logging * Context injection * Automated review * Build guardrails around autonomous AI agents to prevent unsafe or unintended changes. * Develop reusable automation patterns for AI\-assisted development teams. 5\. Browser \& Test Automation * Strong hands\-on experience with **Selenium and Playwright**. * Develop robust browser automation frameworks and reusable automation components. * Automate: * Web applications * Functional testing * Regression testing * Data extraction * Form processing * Login/authentication workflows * Business process automation * Prefer **Playwright** where appropriate for modern web applications. * Implement reliable selectors, waits, retries, parallel execution, screenshots, traces, and failure diagnostics. * Integrate browser automation with AI agents to enable intelligent browser\-based task execution. 6\. n8n \& Workflow Automation * Design and implement business automation workflows using **n8n**. * Integrate n8n with: * REST APIs * Webhooks * Databases * CRM systems * Messaging platforms * LLMs * MCP servers * Internal applications * Build event\-driven workflows and multi\-step automation pipelines. * Implement error handling, retries, logging, monitoring, and workflow observability. * Build AI\-powered workflows combining **n8n \+ LLM \+ Agents \+ APIs \+ MCP**. 7\. AI\-Powered Software Engineering * Integrate AI into the complete software development lifecycle. * Use AI agents for: * Requirement analysis * Architecture analysis * Code generation * Code review * Test generation * Bug investigation * Documentation * Refactoring * Deployment assistance * Build workflows where AI agents can analyze an existing codebase before making changes. * Implement approval\-based workflows for AI\-generated code and production changes. 8\. Production \& Engineering * Design scalable and maintainable AI automation solutions. * Develop APIs and backend services required for AI workflows. * Implement authentication, authorization, secrets management, logging, monitoring, and audit trails. * Work with development teams to integrate AI capabilities into existing enterprise applications. * Ensure AI solutions are reliable, secure, cost\-efficient, and production\-ready. Pay: ₹873,984\.98 \- ₹1,459,619\.55 per year Work Location: In person