AI Developer

Responsibilities

• Design and build AI‑powered solutions using Microsoft’s AI ecosystem, primarily Azure, Git Hub, Copilot Studio, and Azure AI Foundry.
• Develop and integrate conversational copilots, retrieval‑augmented generation (RAG) experiences, and automation workflows into enterprise applications.
• Collaborate closely with product, engineering, security, and business stakeholders to deliver scalable, compliant, and measurable AI capabilities that support utility and energy customers.
• Build and maintain AI solutions leveraging Azure AI Foundry, including model selection, prompt orchestration, evaluation, and deployment patterns, with a focus on reliable and customer‑centric outcomes.
• Develop and configure copilots using Copilot Studio, including topics, actions, plugins/connectors, and inclusive conversation design.
• Implement AI integration patterns such as retrieval‑augmented generation (RAG), tool/function calling, and agent‑based workflows into applications and internal tooling.
• Create and maintain API services (e.g., Azure Functions, App Service, and containerized services) to expose AI capabilities to enterprise business systems.
• Design and implement secure and accountable data access patterns for enterprise knowledge sources, including SharePoint, Azure SQL, and Blob Storage.
• Use Azure Dev Ops and Git Hub for source control, pull requests, code reviews, branching strategies, and release management in a collaborative and agile environment.
• Build CI/CD pipelines that support automated testing, security scanning, and deployments to Azure.
• Apply engineering best practices, including unit and integration testing, telemetry, error handling, performance tuning, and clear documentation.
• Follow secure‑by‑design practices, including identity and access management (Entra ), secrets management (Key Vault), and least‑privilege access.
• Support responsible AI and governance requirements, including logging, auditing, evaluation, content safety, and prompt and security guardrails.
• Partner with security and compliance teams to ensure AI solutions align with enterprise policies and regulatory requirements common in the utilities and energy sector.
• Translate business needs into AI solution designs, user stories, and technical delivery plans that are practical and measurable.
• Work cross‑functionally with product, engineering, and business partners to define success metrics, validate outcomes, and iterate based on feedback and analytics.
• Provide guidance and enablement to teams adopting Copilot Studio and Azure AI Foundry patterns, fostering shared ownership and continuous learning.

• Experience building software solutions using Azure, including at least one of the following:
  Functions, App Service, Storage, SQL, or API Management.
• Hands‑on development experience with Azure Dev Ops and/or Git Hub, including pull request workflows, branching strategies, issue tracking, and CI/CD.
• Experience developing AI‑driven applications, including at least one of the following:
  Copilots, chatbots, or conversational user experiences, Retrieval‑based solutions (RAG) and enterprise search, Prompt engineering and prompt or version management, Tool/function calling or agentic workflows.
• Ability to work with REST APIs and integrate AI solutions with enterprise systems.
• Strong software engineering fundamentals, including data structures, API design, testing, and troubleshooting.
• Clear communication skills with the ability to explain AI concepts to both technical and non‑technical audiences.
• Experience with Copilot Studio, including topics, actions, connectors, publishing, and governance (preferred).
• Experience with Azure AI Foundry, including prompt flows and orchestration, evaluation, deployments, and observability (preferred).
• Familiarity with Azure OpenAI or other large language model providers and model lifecycle concepts (preferred).
• Experience with enterprise identity solutions, including Entra , OAuth2, role‑based access control, and secure data patterns (preferred).
• Knowledge of monitoring and observability tools such as Application Insights, Log Analytics, and dashboards (preferred).
• Experience with Power Platform, Logic Apps, or other integration and automation platforms (preferred).