Location: On-site, 5 days per week
About the Role
We're hiring a hands-on AI Developer with strong expertise in Python or .NET, cloud platforms, and modern data tooling to join our multidisciplinary AI team. You'll work alongside AI engineers/developers and business analysts to build, ship, and iterate on real production AI solutions.
This role is ideal for someone who thrives in a fast-paced environment where they own work end-to-end: prototyping, building, deploying, and refining. If you've come up through a smaller company or startup where you wore multiple hats and shipped real systems, you'll feel right at home.
What You'll Do
·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.
Tech You'll Touch
Core: Python · .NET · 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)
Required Qualifications
·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:
o Azure AI Search (or equivalent vector/semantic search platform — Pinecone, Weaviate, pgvector, Elasticsearch with vector, AWS Kendra/OpenSearch)
o Vector databases
o Semantic search
o 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.
Nice to Have
·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.
About the Role
We're hiring a hands-on AI Developer with strong expertise in Python or .NET, cloud platforms, and modern data tooling to join our multidisciplinary AI team. You'll work alongside AI engineers/developers and business analysts to build, ship, and iterate on real production AI solutions.
This role is ideal for someone who thrives in a fast-paced environment where they own work end-to-end: prototyping, building, deploying, and refining. If you've come up through a smaller company or startup where you wore multiple hats and shipped real systems, you'll feel right at home.
What You'll Do
·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.
Tech You'll Touch
Core: Python · .NET · 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)
Required Qualifications
·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:
o Azure AI Search (or equivalent vector/semantic search platform — Pinecone, Weaviate, pgvector, Elasticsearch with vector, AWS Kendra/OpenSearch)
o Vector databases
o Semantic search
o 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.
Nice to Have
·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.
