Responsibilities

Role Summary

We are seeking a Senior AI Engineer to build and support production-grade decisioning and data processing systems in a highly rules-driven enterprise environment.
This is a hands-on engineering role focused on Python-based decision pipelines, business rule implementation, and CI/CD delivery. Strong experience with Databricks and Azure AI Foundry is essential for building scalable enterprise AI and data solutions. Exposure to enterprise AI or LLM capabilities, including OpenAI models, may occur when required, but the primary emphasis is on reliable, maintainable, production systems rather than experimentation or research.

Core Responsibilities
Design, build, and support scalable Python-based processing and decisioning pipelines using Databricks, PySpark, and Pandas.
Develop and maintain enterprise data processing workflows within the Databricks platform.
Translate complex business rules and domain logic into clean, testable, and maintainable decisioning systems.
Build modular, reusable components suitable for orchestrated, production workflows.
Develop and integrate AI-powered solutions using Azure AI Foundry, including enterprise AI, OpenAI, and other LLM services when required.
Integrate enterprise AI or LLM services (including OpenAI models) when needed, including basic prompt/template configuration and structured output parsing.
Apply standard safety and compliance controls (e.g., PII handling, input/output validation).
Integrate internal and external APIs with robust error handling and retry strategies.
Implement data validation, structured logging, and monitoring to support production observability and troubleshooting.
Participate in Git-based development, including branching, pull requests, code reviews, and conflict resolution.
Build and maintain CI/CD pipelines in Azure DevOps, including release workflows and deployment monitoring.
Support and troubleshoot live production systems.

Required Skills & Experience
Strong, hands-on experience with Python engineering for production systems.
Hands-on experience with Databricks for enterprise data engineering, notebook development, and production data pipelines.
Hands-on experience with Azure AI Foundry for developing, deploying, and integrating enterprise AI solutions.
Advanced proficiency with PySpark and Pandas.
Proven experience implementing business rules, decision logic, or rule-driven systems.
Experience working with OpenAI, Agentic AI systems, or AI-assisted workflows.
Experience integrating and working with OpenAI or other large language models (LLMs) in enterprise applications.
Solid understanding of Git-based delivery models.
Hands-on experience with Azure DevOps, including CI/CD pipelines and deployment monitoring.
Experience supporting enterprise production workloads.

Nice to Have
Experience in utilities, energy, or other rules-heavy domains.
Familiarity with workflow orchestration tools (ADF, Airflow, etc.).
Prior exposure to applied AI systems in enterprise environments.