Principal AI Developer
Principal AI Developer
Posted 8 days ago
SENIORITY
Senior
About the role
- Azure
- Databricks (data platform)AI stack: Azure OpenAI
- Azure AI Foundry
- Azure AI Search
- Microsoft Copilot Studio
- Semantic Kernel
- Vector Databases
- RAG (Retrieval-Augmented Generation)
- Semantic Search
- Agentic AI
- MCP (Model Context Protocol)
- Design, develop, deploy, and maintain AI solutions using Python and/or .NET.
- Build AI agents using Microsoft Copilot Studio or the Semantic Kernel Agent Framework.
- Build and optimize cloud-native applications on Azure.
- Work with large-scale data in Databricks.
- Partner with AI engineers/developers and business analysts to turn ideas and experiments into production systems.
- Apply critical thinking to evaluate model performance, troubleshoot complex issues, and improve system efficiency.
- Communicate clearly with both technical and non-technical stakeholders.
- Prototype quickly, test rigorously, and iterate often.
- Bachelor's degree or equivalent experience, with relevant job experience commensurate with the selected job level (see below).
- Professional experience building production systems with Python or. NET (proficiency in both is a strong plus).
- Strong working knowledge of cloud services and architecture patterns — Azure preferred (or equivalent experience in AWS or GCP, with willingness to ramp on Azure).
- Hands-on experience building RAG (Retrieval-Augmented Generation) pipelines.
- Hands-on experience building AI agents with Microsoft Copilot Studio, Semantic Kernel Agent Framework, or an equivalent agent framework (e.g., LangGraph, AutoGen, CrewAI).
- Hands-on experience with at least two of the following: Azure AI Search (or equivalent vector/semantic search platform — Pinecone, Weaviate, pgvector, Elasticsearch with vector, AWS Kendra/OpenSearch) Vector databases Semantic search Agentic AI systems (multi-step reasoning, tool use, orchestration)
- Comfort working with SQL and large-scale data platforms (Databricks experience is a plus, but the syntax is approachable if you know SQL).
- Excellent communication and critical-thinking skills.
- Background in a smaller company or startup environment with significant ownership of technical work. Required experience is commensurate with the selected job level:
- The Senior Specialist level requires a Bachelor's degree or equivalent experience and 5-8 years of relevant job related experience.
- The Lead Specialist level requires a Bachelor's degree or equivalent experience and 8+ years of relevant job related experience.
- The Principal Specialist level requires a Bachelor's degree or equivalent experience and 10+ years of relevant job related experience.
- Proficiency in both Python and. NET.
- Direct hands-on experience with Microsoft Copilot Studio and/or Semantic Kernel specifically.
- Hands-on experience with Databricks specifically.
- Practical ML experience (model training, evaluation, deployment).
- Familiarity with Azure AI Foundry (or equivalent — AWS Bedrock, Google Vertex AI) and Azure OpenAI (or equivalent managed LLM service) in production.
- Experience with MCP (Model Context Protocol) or similar agent-tooling standards.
- Natural Gas Pipeline or Energy Industry work experience is a plus.
- Usually, normal office working conditions.
- This is an on-site role, worked in person at the office 5 days per week during business hours.
- Must be able to remain in a stationary position 50% of the time due to prolonged periods of sitting or standing.
- Occasional overnight travel may be required to other business locations within the company.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
