Associate Staff Engineer (Python Agentic Workflows)

Job Description Requirements - Experience : 4+ years - Strong experience in full-stack software development with strong expertise in Python backend development and modern JavaScript frontend frameworks such as React, Next.js, or equivalent. - Strong programming skills in Python with experience building scalable backend services, REST APIs, and enterprise applications. - Hands-on experience developing production-grade AI applications using Large Language Models (LLMs), including function calling, tool usage, and agentic AI workflows. - Strong understanding of prompt engineering, system prompt design, tool definition, prompt optimization, and multi-step AI orchestration. - Experience designing and implementing autonomous AI agents capable of reasoning, retrieval, and enterprise task execution. - Experience integrating enterprise applications through REST APIs, including platforms such as SAP, Microsoft Graph, SharePoint, relational databases, and workflow systems. - Strong frontend development experience using React, Next.js, or similar frameworks to build responsive dashboards and interactive user interfaces. - Experience developing real-time applications, enterprise dashboards, and AI-powered web applications. - Experience deploying applications on cloud or on-premises environments with knowledge of SSO authentication, enterprise networking, and security best practices. - Hands-on experience with CI/CD pipelines, version control systems, and modern software deployment practices. - Familiarity with AI-assisted development tools such as GitHub Copilot, Cursor, Claude Code, or similar productivity tools is preferred. - Experience building enterprise automation platforms, internal business tools, or operational dashboards is an advantage. - Exposure to Retrieval-Augmented Generation (RAG), vector databases, document processing pipelines, embeddings, and semantic search is desirable. - Strong understanding of software architecture, API integration, and scalable application development principles. - Excellent analytical, troubleshooting, and problem-solving skills with the ability to work independently in a fast-paced, evolving environment. - Strong verbal and written communication skills with the ability to collaborate effectively across cross-functional teams. - Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline. - Experience with DevOps practices, containerization, cloud platforms, and AI application deployment is an added advantage. Responsibilities - Design, develop, and deploy AI agents capable of autonomous reasoning, data retrieval, decision-making, and task execution across enterprise applications and business systems. - Build and optimize agentic AI workflows using LLMs, function calling, tool orchestration, and multi-step reasoning to automate complex business processes. - Develop robust Python backend services that orchestrate AI interactions, manage multi-turn conversations, execute enterprise API calls, and deliver structured, reliable responses. - Design, implement, and maintain modern frontend applications using React, Next.js, or equivalent frameworks to provide intuitive dashboards, real-time AI interactions, and user-friendly interfaces. - Develop one-click automation workflows, interactive dashboards, formatted response views, and conversational interfaces for enterprise users. - Integrate AI agents with enterprise platforms such as SAP, Microsoft SharePoint, Microsoft Graph, relational databases, approval systems, and other business applications through secure APIs. - Design and implement prompt engineering strategies, system prompts, tool definitions, and orchestration logic to ensure accurate, secure, and reliable AI agent behavior. - Develop intelligent enterprise automation solutions for document retrieval, business reporting, operational alerting, workflow automation, approval management, and data analysis. - Deploy and maintain AI applications on cloud or on-premises infrastructure with Single Sign-On (SSO), secure authentication, CI/CD pipelines, and enterprise networking configurations. - Collaborate with business stakeholders, product teams, architects, and developers to understand business requirements and translate them into scalable AI-powered solutions. - Optimize AI agent performance, reliability, scalability, and user experience through continuous testing, monitoring, debugging, and performance tuning. - Ensure AI applications follow enterprise security, governance, and software engineering best practices. - Maintain technical documentation, architecture designs, API integrations, deployment guides, and operational documentation. - Stay updated with emerging AI technologies, LLM capabilities, and enterprise automation trends to continuously improve solution capabilities.