We are seeking a talented and detail-oriented L3 Agentic Developer with strong hands-on Python experience and expertise in Microsoft Azure. This role will focus on designing, developing, and deploying robust, autonomous AI agents leveraging the latest agentic design patterns and cloud-native services. The ideal candidate will be a proactive problem-solver, adept at debugging complex systems, and knowledgeable about secure cloud principles.

Key Responsibilities :

- Agent Development : Design, build, and deploy sophisticated AI agents using Python and frameworks like LangGraph, implementing complex DAGs with conditional edges and autonomous tool-calling capabilities.

- Azure Integration : Architect and implement solutions leveraging core Azure services, including deploying application logic via Azure Functions and integrating with monitoring tools such as Application Insights or Log Analytics Workspace (LAW).

- Secure Infrastructure : Implement secure cloud practices, including managing service principles, user principles, and Managed Identities for secure, credential-free service interaction.

- Debugging & Troubleshooting : Utilize strong debugging skills to identify and resolve complex issues across local environments and cloud deployments, proficient with integrated debuggers and console-based methods.

- Prompt Engineering : Apply advanced prompt engineering techniques, understanding trade-offs between different methods (e.g., few-shot prompting, chain-of-thought, tool schema provision) to optimize LLM performance and reliability.

- Design Patterns : Drive the adoption of agentic design patterns, specifically implementing the "LLM as a decision maker" pattern where the model dynamically selects and executes tools based on provided schema and context.

Required Qualifications :

- Experience : Proven hands-on experience as a Python Developer building production-grade applications.

- Cloud Proficiency : Strong experience with Cloud platforms, preferably Microsoft Azure (AWS or GCP experience is also valued).

Technical Skills :

- Proficiency with AI orchestration frameworks such as LangGraph.

- Experience deploying and managing applications on Azure Functions.

- Knowledge of monitoring tools like Azure App Insights or Log Analytics.

- Deep understanding of secure identity management within cloud environments (Service Principals, Managed Identities).

- Expert-level debugging skills in various environments.

AI Knowledge :

- Demonstrated understanding of prompt engineering techniques and core agentic design patterns.

Preferred (Good to Have) Qualifications :

- Development Tools : Familiarity with the VS Code IDE environment.

- Cloud Networking : Knowledge of Azure networking components (VNets, Subnets, DNS configurations).

- DevOps/IaC : Experience creating simple CI/CD pipelines or managing infrastructure as code using Bicep or Terraform.

- Performance Optimization : Experience with Python asynchronous programming (asyncio), multi-processing, or multi-threading concepts.

- Emerging Tech : Awareness of concepts like the Model Context Protocol (MCP).

Level 3 (L3) Expectations :

An L3 engineer is expected to operate with significant autonomy, own medium-to-large features end-to-end, provide technical guidance to junior team members, troubleshoot complex, non-obvious issues across system boundaries, and contribute actively to architectural discussions.