Essential Duties and Responsibilities

To perform this job successfully, an individual must be able to perform each essential job duty satisfactorily. The requirements for this position are listed below:

• 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.

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job.

• 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.