Generative AI Engineer

Agentic Developer (L3) - Python & Azure FocusWe 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.

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