Data Scientist with .Net experience

Innova Solutions•Charlotte, NC

10h•Hybrid

About The Position

A client of Innova Solutions is immediately hiring for a Senior Python / AI Platform Engineer with .Net experience. This is a full-time, 12-month contract (W2) role with possible extension, located in Charlotte, NC, requiring 3 days hybrid on-site. As a Senior Python / AI Platform Engineer with .Net experience Developer, you will be responsible for a variety of tasks related to developing and deploying AI and data-driven solutions.

Requirements

Software Engineering, AI/ML Engineering, Data Engineering, or related disciplines with strong expertise in .NET/C# application development and backend engineering.
Strong hands-on experience in Python development for AI/ML, data processing, automation, and platform engineering initiatives.
Experience partnering with Data Science teams to productionize Machine Learning, Generative AI, and Predictive Analytics solutions in enterprise environments.
Expertise building and integrating scalable REST APIs using Python (FastAPI) and .NET technologies.
Hands-on experience with Azure OpenAI, OpenAI APIs, LangChain, LangGraph, RAG frameworks, Vector Databases, Embeddings, and AI application deployment.
Strong understanding of cloud-native application development and deployment using Microsoft Azure, including Azure App Services, Azure Functions, Azure AI Services, Azure Data Factory, and related services.
Experience with containerization and orchestration technologies including Docker, Kubernetes, and OpenShift.
Strong data engineering background with experience building and optimizing ETL/ELT pipelines, working with SQL, Oracle, Spark/PySpark, and enterprise data platforms.
Knowledge of modern data platforms including Microsoft Fabric, OneLake, Data Warehouse, and Lakehouse architectures.
Experience implementing CI/CD pipelines using Azure DevOps, GitHub Actions, and DevOps best practices.
Solid understanding of software engineering principles including design patterns, code reviews, testing strategies, monitoring, logging, performance optimization, and production support.
Experience with enterprise security practices including OAuth, Key Vault, Secrets Management, Data Governance, and PII compliance requirements.
Ability to troubleshoot and resolve complex application, platform, and data pipeline issues in production environments.
Strong communication skills with the ability to collaborate effectively with Data Scientists, Product Owners, Architects, and cross-functional engineering teams.
Experience working in Agile/Scrum environments with a focus on delivering scalable, secure, and highly available technology solutions.

Nice To Haves

Exposure to technologies such as React, Databricks, MLflow, Snowflake, Semantic Kernel, Azure AI Search, Neo4j, Elasticsearch, Flask, and Django is highly preferred.

Responsibilities

Strong experience in C#/.NET development, including .NET Core, ASP.NET, Web APIs, microservices, and enterprise application development.
Hands-on expertise in Python development with experience building scalable applications, automation solutions, and AI-powered services.
Experience productionizing and deploying Generative AI, Machine Learning, and Predictive Analytics solutions from proof-of-concept to enterprise-scale production environments.
Strong knowledge of Azure OpenAI, OpenAI APIs, LangChain, LangGraph, RAG, Embeddings, Vector Search, and AI model operationalization.
Experience building and supporting scalable REST APIs using FastAPI, Python, and .NET technologies.
Solid experience with Microsoft Azure, including cloud-native application development, deployment, and platform engineering.
Hands-on experience with Docker, Kubernetes, OpenShift, and containerized application deployment.
Strong data engineering background with experience in SQL, Oracle, ETL/ELT processes, Spark/PySpark, Data Modeling, and Data Pipeline Development.
Experience working with modern data platforms such as Microsoft Fabric, OneLake, Data Warehouses, and Lakehouse architectures.
Knowledge of Azure Data Factory, Airflow, or similar orchestration platforms for workflow automation and data pipeline management.
Experience implementing and managing CI/CD pipelines using Azure DevOps, GitHub Actions, and DevOps best practices.
Strong understanding of application monitoring, logging, alerting, and production support, including Application Insights and operational excellence practices.
Familiarity with enterprise security standards including OAuth, Key Vault, Secrets Management, PII protection, and Data Governance.
Ability to collaborate effectively with Data Scientists, Engineers, Architects, and Business Stakeholders to deliver scalable AI and data-driven solutions.
Strong analytical and problem-solving skills with experience troubleshooting complex application, platform, and data engineering challenges.
Experience working in Agile/Scrum environments with a focus on quality, scalability, security, and continuous improvement.