Sr Python / AI Backend Engineer (Not ML or Data Only)

• Design and develop scalable backend applications and services using Python.
• Build production-grade REST APIs, microservices, asynchronous services, and event-driven applications.
• Design backend components supporting AI-enabled workflows and enterprise applications.
• Develop integrations with databases, queues, enterprise systems, APIs, and cloud services.
• Implement secure, scalable, observable, and maintainable production services.
• Participate in architecture, API design, code reviews, automated testing, and engineering standards., * Build real-world AI capabilities rather than simply wrapping third-party AI APIs.
• Develop applications using LLMs, RAG, embeddings, vector search, agents, tool calling, and AI workflow orchestration.
• Build AI services that process structured and unstructured enterprise information.
• Implement document understanding, classification, extraction, summarization, reasoning, and automation workflows.
• Design retrieval pipelines including chunking, indexing, embeddings, metadata filtering, reranking, and grounding.
• Develop AI agents capable of interacting with APIs, enterprise applications, databases, and business workflows.
• Implement prompt management, model selection, context management, guardrails, and structured outputs.
• Build evaluation frameworks to measure AI solution quality, accuracy, hallucination, latency, and cost.
• Improve AI application performance through caching, model routing, retrieval optimization, and related techniques.

Azure & AI Platform Engineering

• Design and implement AI solutions using Microsoft Azure.
• Build and deploy AI applications using Azure AI Foundry.
• Work with Azure OpenAI Service and other Azure AI services.
• Design enterprise search and RAG solutions using Azure AI Search.
• Build and integrate data ingestion and orchestration pipelines using Azure Data Factory (ADF).
• Integrate Azure data services with Python-based backend and AI applications.
• Understand Azure identity, networking, security, storage, monitoring, and application hosting concepts.
• Deploy applications using Azure services such as Azure App Service, Azure Functions, Azure Container Apps, AKS, or similar platforms.
• Implement logging, monitoring, tracing, and operational controls using Azure-native capabilities., * Integrate AI services into existing enterprise applications and backend platforms.
• Expose existing business functionality securely to AI-powered applications and agents.
• Design interfaces between Python AI services and existing enterprise systems.
• Integrate Python-based AI services with .NET/C# applications where required.
• Support modernization initiatives where AI capabilities are introduced into existing enterprise platforms.

Cloud & Production Engineering

• Build containerized applications using Docker and modern CI/CD practices.
• Deploy scalable backend and AI workloads into Azure.
• Implement monitoring, logging, tracing, resiliency, security, and operational controls.
• Work closely with DevOps and platform engineering teams to productionize AI workloads., The ideal candidate is a backend software engineer first, with strong applied AI and Azure engineering capability.

We are particularly interested in candidates who have:

• Built substantial backend systems in Python, not primarily notebooks or data pipelines.
• Written production application code rather than focusing predominantly on analytics or experimentation.
• Implemented actual AI logic and AI workflows rather than only calling an LLM API.
• Built APIs, services, agents, RAG systems, document intelligence solutions, or AI automation capabilities deployed into production.
• Built AI solutions using Azure AI Foundry and Azure OpenAI.
• Used Azure Data Factory to orchestrate data movement and ingestion where needed as part of enterprise solutions.
• Worked with Azure-native services to build secure, scalable, production-grade applications.
• Worked on enterprise-grade software requiring scalability, security, reliability, and maintainability.
• Experience with .NET/C# is a significant advantage.

Candidates Who May Not Be the Best Fit

This role is not targeted primarily toward candidates whose experience is predominantly:

• Data Engineering / ETL
• Azure Data Factory development without backend software engineering
• Data Warehousing
• Spark / Databricks pipeline development
• BI / Analytics
• Data Science and statistical modeling
• Traditional ML model training without significant software engineering
• MLOps without hands-on application development
• AI API integration without deeper AI application engineering
• Notebook-based experimentation without production backend development

Preferred Technology Profile

Primary

• Python
• FastAPI / Flask / Django
• REST APIs / Microservices
• Microsoft Azure
• Azure AI Foundry
• Azure OpenAI
• Azure AI Search
• Azure Data Factory
• SQL
• LLM / Generative AI
• RAG
• AI Agents
• Vector Search
• Docker / Cloud-native development

Strong Plus

• C#
• .NET / ASP.NET Core
• Semantic Kernel
• Azure Functions
• Azure Container Apps / AKS
• Azure Service Bus
• Kubernetes
• Event-driven architectures

Algoworks is looking for a Sr Python / AI Backend Engineer with strong hands-on experience building production-grade backend applications using Python, combined with practical experience developing AI-powered enterprise solutions beyond basic API integrations.

The ideal candidate is a strong backend software engineer who understands application architecture, APIs, distributed systems, databases, and cloud-native development, while also having hands-on experience implementing AI capabilities such as LLM applications, RAG, agents, embeddings, document intelligence, AI workflows, evaluation, and model-driven automation.

Strong knowledge of the Microsoft Azure ecosystem is required, including Azure AI Foundry, Azure OpenAI, Azure Data Factory, Azure AI Search, and related Azure services.

Experience with .NET / C# is a strong plus, particularly for candidates who have worked in enterprise environments where Python-based AI services need to coexist and integrate with existing .NET platforms., * 5+ years of software engineering / backend development experience.

• Strong hands-on expertise with Python.
• Strong experience with Python backend frameworks such as:
• FastAPI
• Flask
• Django
• Strong understanding of:
• REST APIs
• Microservices
• Distributed systems
• Authentication and authorization
• Database integration
• Asynchronous processing
• Messaging and queues
• Error handling and resiliency
• Strong SQL and relational database fundamentals.
• Practical experience building production AI / Generative AI applications.
• Hands-on experience with multiple areas including:
• Large Language Models
• RAG
• Vector databases
• Embeddings
• AI agents
• Function/tool calling
• Prompt engineering
• Document intelligence
• AI workflow orchestration
• AI evaluation and testing
• Hands-on experience with Microsoft Azure.
• Experience with Azure AI Foundry.
• Experience with Azure OpenAI Service.
• Experience with Azure Data Factory (ADF).
• Experience with Azure AI Search or comparable enterprise search/vector search technologies.
• Understanding of Azure application hosting, security, identity, networking, and monitoring.
• Strong software engineering fundamentals including OOP, design patterns, testing, source control, and CI/CD.

Strongly Preferred

• Hands-on development experience with C# and .NET / ASP.NET Core.
• Experience working on enterprise platforms containing both Python and .NET services.
• Strong Azure architecture experience.
• Experience with:
• Azure Functions
• Azure Container Apps
• Azure App Service
• AKS
• Azure Service Bus
• Azure Storage
• Key Vault
• Application Insights
• Experience with agent and AI orchestration technologies such as:
• Microsoft Semantic Kernel
• Azure AI Foundry Agent Service
• LangChain
• LangGraph
• AutoGen
• Similar agentic frameworks
• Experience with vector and search technologies such as:
• Azure AI Search
• Pinecone
• Qdrant
• Weaviate
• pgvector
• Elasticsearch / OpenSearch
• Experience with Docker, Kubernetes, GitHub Actions, or Azure DevOps.
• Experience with event-driven technologies such as Kafka, RabbitMQ, Azure Service Bus, or similar platforms., Senior Python Backend Engineer + Applied AI Engineer + Azure Engineer

The candidate should be capable of independently taking an AI use case through:

Business Requirement * Backend Architecture * Azure Architecture * AI Design * Python Implementation * Data Integration * Enterprise Integration * AI Evaluation * Production Deployment