Senior Artificial Intelligence Engineer

Apidel Technologies; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Apidel Technologies is seeking a Sr. AI Engineer to design, develop, and deploy Data & AI solutions on Microsoft Azure.

The role focuses on enterprise-scale Data & AI platforms, pipelines, and AI applications built in collaboration with data scientists and business stakeholders. Candidates should have hands-on experience with Azure, Databricks, Foundry, Generative AI, and agent-based AI to scale enterprise solutions.

Qualifications

• Proficiency in Python and SQL, with hands-on data engineering concepts.
• Experience with PySpark or distributed data processing frameworks.
• Experience developing REST APIs, scripts, or cloud-based applications.

Responsibilities

• Assist in building and maintaining Data & AI platforms, applications, and services.
• Develop and support data ingestion pipelines, ETL/ELT processes, and analytics workflows.
• Implement AI and Generative AI solutions using Azure AI services, Azure OpenAI, Azure Foundry, Agent Bricks, and Genie Spaces.
• Support the development of RAG-based applications, AI agents, and LLM-powered solutions.
• Contribute to data lake, lakehouse, and data warehouse implementations.
• Monitor data and AI workloads and assist in troubleshooting performance and operational issues.
• Follow best practices for security, governance, compliance, and Responsible AI.
• Participate in CI/CD, DevOps, and Infrastructure as Code (IaC) activities.
• Collaborate with cross-functional teams to understand business requirements and deliver technical solutions.
• Continuously learn and adopt emerging Data & AI technologies and engineering practices.

Skills

Python

SQL

PySpark

REST APIs

Tools

Azure

Databricks

Foundry

Azure OpenAI

Agent Bricks

Genie Spaces

MLflow Model Registry

Unity Catalog

Azure AI Services

Vector Search

Job description

Sr. AI Engineer

Position Summary

We are seeking a motivated Sr. AI Engineer to support the design, development, and deployment of Data & AI solutions on Microsoft Azure. This role is ideal for engineers with foundational experience in Data Engineering, AI/Generative AI, Cloud Technologies, and Software Development who are looking to grow their expertise in enterprise-scale Data & AI platforms.

The AI & Data Engineer will work closely with senior engineers, architects, data scientists, and business stakeholders to build data pipelines, AI applications, and analytics solutions while gaining hands‑on experience with modern Azure Data & AI services.

Required Qualifications

Technical Skills

• Proficiency in Python and working knowledge of SQL.
• Basic understanding of data engineering concepts and data processing pipelines.
• Familiarity with PySpark or distributed data processing frameworks.
• Experience developing REST APIs, scripts, or cloud‑based applications.

We are looking for a hands‑on AI Solution Lead with strong expertise in Azure, Databricks, Microsoft Foundry, Generative AI, and Agentic AI to build and scale enterprise AI solutions.

• Microsoft Azure & Microsoft Foundry / Azure AI Foundry
• Azure Databricks, Agent Bricks & Genie
• Ml flow Model Registry, Evaluation & Agent Tracing
• Unity Catalog – Governance, Security & Attribute‑Based Access Control
• Azure OpenAI & Azure AI Services
• RAG, LLMs, Vector Search & Hybrid Search
• AI Agents, Agent Memory, Tools & Guardrails
• Foundry Tracing & Evaluation
• Python, PySpark & SQL
• Azure AI Search / Cognitive Search
• Spark debugging & performance optimization
• CI/CD, Azure DevOps & cloud security

Key Responsibilities

• Assist in building and maintaining Data & AI platforms, applications, and services.
• Develop and support data ingestion pipelines, ETL/ELT processes, and analytics workflows.
• Implement AI and Generative AI solutions using Azure AI services, Azure OpenAI, Azure AI Foundry, Agent Bricks, and Genie Spaces.
• Support the development of RAG‑based applications, AI agents, and LLM‑powered solutions.
• Contribute to data lake, lakehouse, and data warehouse implementations.
• Monitor data and AI workloads and assist in troubleshooting performance and operational issues.
• Follow best practices for security, governance, compliance, and Responsible AI.
• Participate in CI/CD, DevOps, and Infrastructure as Code (IaC) activities.
• Collaborate with cross‑functional teams to understand business requirements and deliver technical solutions.
• Continuously learn and adopt emerging Data & AI technologies and engineering practices.

AI & Data

• Foundational knowledge of Machine Learning, AI, and Generative AI concepts.
• Understanding of Large Language Models (LLMs), embeddings, vector databases, and Retrieval‑Augmented Generation (RAG).
• Familiarity with AI orchestration frameworks such as LangChain, Semantic Kernel, LangGraph, or similar technologies.
• Basic understanding of data modeling, analytics, and enterprise data platforms.
• Awareness of MLOps, AI governance, and Responsible AI principles.

DevOps & Security

• Understanding of CI/CD concepts and Git‑based development workflows.
• Basic knowledge of cloud security, identity management, and API security.
• Familiarity with governance and compliance considerations in enterprise environments.