Join #Ensiteam!

We are a company focused on custom software development and have been in the market for over 19 years. At Ensitech we are dedicated to finding highly specialized talent to work with large companies in the United States, Europe, and Canada.

Each one of our collaborators works with different teams and colleagues around the world, in the design and commercialization of software. We look forward to having you as part of our team in the role of Software Azure Databricks Engineer

We are looking for a Azure Databricks Engineer to support our delivery organization with modern data platforms and AI initiatives. This is not a traditional data engineering role—it is an engineering-focused position centered on building scalable pipelines, governed data products, analytics services, and AI-enabled solutions on Azure and Databricks. You will design, build, and optimize lakehouse architectures, orchestration frameworks, and production-ready solutions that help clients modernize data estates and operationalize AI across the enterprise.

What you will do

Architect Agentic Systems: Design and implement multi-agent systems using frameworks like LangGraph, CrewAI, or AutoGen to automate complex, multi-step business processes.
• Full Stack Execution: Build responsive, AI-integrated front ends (React/Next.js) and robust back end microservices (FastAPI/Python) that leverage Azure Databricks.
• Modernize Apps: Lead “AI-first” refactoring of legacy applications, moving from deterministic
code to probabilistic, agent-driven workflows.
• Engineered Integration: Develop and secure RAG (Retrieval-Augmented Generation) pipelines, integrating vector databases and enterprise data sources via Databricks.
• API Ecosystems: Build and maintain high-performance APIs and GraphQL layers that serve as the “hands and eyes” for your AI agents.
• DevOps; AIOPs: Implement CI/CD for LLMs, including automated evaluation (LLM-as-a-judge), monitoring for drift, and managing deployment on Azure Kubernetes Service (AKS) or Container
Apps.

Requirements

Experience: 3–7 years of experience in Azure data engineering, Databricks solution delivery, or modern cloud platform engineering. The ideal candidate can own deliverables and operate with minimal oversight. They should have broad proficiency across the delivery lifecycle—including requirements translation, design, build, testing, deployment, and support—and be able to contribute hands-on, explain solutions clearly, and implement effectively.
Deep expertise in at least one core domain such as Databricks engineering, data pipelines, cloud architecture, DevOps, or analytics engineering is expected.
The AI Stack:
◦ (Required) Hands-on experience building with AI. With deep understanding of Agentic coding tools, strengths and weaknesses & capabilities.
◦ (Required) Deep understanding of MCP/A2A, Agent frameworks.
◦ (Preferred) Hands-on experience with LLM orchestration frameworks
(LangChain/LangGraph) and prompt engineering.
The Tech Stack: The ideal candidate can take a greenfield solution from an empty repository to full CI/CD delivery of the entire solution to production scale. You don’t have to be an expert in every facet of this, but you must be proficient to the level of being able to review code, design review solutions, etc.
◦ (Required) Proficiency in Python
◦ (Required) Proficiency in at least one Web-based front-end stack
◦ (Required) Deep understanding of Security and Identity Management
◦ (Required) Deep understanding of Infrastructure as Code (IAC). Proficient in at least one IAC tool such as Terraform
◦ (Required) Deep understanding of Version Control Systems and CI/CD (Git/Github preferred), build processes, security scanning, licensing, etc.
◦ (Preferred) Demonstrated expertise in at least one high-level language (.net, java, C++).
Demonstrated Mastery: Position will require certifications in Azure Databricks. You will be expected to get and maintain at least one Associate Level Azure or Databricks within 30 days of hiring and expected to achieve others based on company needs; roles.
◦ (Preferred) At least one associate level certification in Azure or Databricks.
◦ (Preferred) At least one expert level certification in Azure or Databricks.
Distributed Systems: Understanding of asynchronous patterns, message brokers (Service Bus/Kafka), and state management in agentic loops.
Consulting Mindset: Ability to white-board complex architectures with clients and translate “business problems” into “agentic solutions.”

Bonus Points / Nice to have

Experience with Vector Databases (Pinecone, Weaviate, or Azure AI Search).
Knowledge of Semantic Kernel or building custom GPT Actions/Tools.
Experience in Energy or Industrial sectors (OT data, IoT, or complex supply chain).
Familiarity with MLflow for tracking experiments and model deployment.

What do we offer?

100% remote opportunity.
Competitive salary and benefits.
Custom benefit package aligned to your experience and your needs.
Working with foreign clients.

Software Engineer – Azure Databricks & ...