Job Description: Senior Python Backend / Platform Engineer — AI Applications

Job Summary

We are looking for a strong Python Backend / Platform Engineer who can design and build enterprise-grade backend systems, APIs, integrations, and cloud-deployed services.

This role is intended for a hands-on developer who is already strong in backend engineering and can grow into an AI Application Engineer through a structured 2–3 month bridge training program. The selected candidate will work on modern backend systems involving APIs, cloud services, databases, integrations, and eventually LLM-powered applications, RAG pipelines, agent workflows, and AI orchestration frameworks.

The ideal candidate should be able to take a high-level design and convert it into a clear low-level design, implementation plan, working code, tests, and deployable services. In some cases, the candidate may also be expected to contribute to high-level system design under architectural guidance.

Role Objective

The objective of this role is to hire a strong backend engineer who can:

·       Build reliable Python-based backend services and APIs.

·       Work with databases, cloud platforms, containers, and CI/CD pipelines.

·       Understand system design and translate designs into implementation.

·       Deliver production-quality backend components independently.

·       Undergo bridge training to become productive in AI application engineering.

·       Build enterprise AI applications involving LLM APIs, RAG, agents, orchestration, and AI observability.

Key Responsibilities

·       Design, develop, test, and maintain backend applications and services using Python.

·       Build RESTful APIs using frameworks such as FastAPI, Flask, or Django.

·       Convert high-level designs into low-level designs, modules, APIs, data models, and implementation tasks.

·       Contribute to high-level design discussions under the guidance of architects or senior technical leads.

·       Design API contracts including request/response models, validation rules, error handling, pagination, and versioning.

·       Work with OpenAPI/Swagger specifications for API documentation and contract-driven development.

·       Implement secure API authentication and authorization using OAuth2, JWT, or similar mechanisms.

·       Work with relational databases such as PostgreSQL or MySQL for schema design, querying, transactions, and performance tuning.

·       Build integrations with enterprise applications, cloud services, APIs, and data platforms.

·       Containerize applications using Docker.

·       Support deployment of backend services to cloud environments, preferably Azure.

·       Contribute to CI/CD pipelines using GitHub Actions, Azure DevOps, or similar tools.

·       Write unit tests, integration tests, and API-level tests.

·       Participate in code reviews, debugging, troubleshooting, and performance optimization.

·       Implement logging, monitoring, metrics, and tracing practices for backend services.

·       Collaborate with architects, project managers, business analysts, frontend developers, data engineers, and AI engineers.

·       Learn and apply AI engineering concepts including LLM APIs, RAG, LangChain, LangGraph, vector search, evaluation, and AI observability.

Required Technical Skills

Backend Engineering

·       Strong hands-on experience in Python backend development.

·       Experience with one or more Python web/API frameworks:

o   FastAPI

o   Flask

o   Django

·       Strong understanding of backend application structure, modular code, error handling, configuration management, and service-layer design.

·       Ability to build production-grade APIs and backend services.

API Design & Integration

·       Strong understanding of RESTful API design.

·       Experience with:

o   Resource modeling

o   HTTP methods and status codes

o   Pagination

o   Filtering and sorting

o   Request validation

o   Error response design

o   API versioning

·       Experience consuming and integrating with third-party APIs.

·       Familiarity with OpenAPI/Swagger.

·       Understanding of API authentication and authorization using OAuth2, JWT, API keys, or similar approaches.

System Design

·       Ability to understand high-level architecture and convert it into low-level design.

·       Ability to create component-level designs, module structures, data models, API contracts, and integration flows.

·       Understanding of common backend design patterns.

·       Ability to reason about scalability, maintainability, security, performance, and failure handling.

·       Ability to document design decisions clearly.

Databases

·       Strong working knowledge of PostgreSQL or MySQL.

·       Ability to design tables, relationships, indexes, and queries.

·       Understanding of transactions, constraints, joins, query optimization, and migrations.

·       Familiarity with NoSQL/document databases such as Cosmos DB is an advantage.

Cloud & DevOps

·       Working knowledge of cloud platforms, preferably Azure.

·       Exposure to services such as Azure App Service, Azure Functions, Azure Container Apps, Azure API Management, Azure Storage, or similar services.

·       Experience with Docker.

·       Basic understanding of Kubernetes concepts; exposure to AKS or GKE is preferred.

·       Experience with Git-based development workflows.

·       Understanding of CI/CD concepts using GitHub Actions, Azure DevOps, or similar tools.

·       Familiarity with container registries such as Azure Container Registry, GitHub Container Registry, or GCP Artifact Registry.

Testing & Quality

·       Experience writing unit tests and integration tests.

·       Familiarity with Python testing frameworks such as pytest or unittest.

·       Ability to test APIs using tools such as Postman, Swagger UI, or automated API tests.

·       Good debugging and troubleshooting skills.

·       Ability to write clean, maintainable, and reviewable code.

Preferred Technical Skills

The following skills are preferred but not mandatory:

·       TypeScript or JavaScript backend development using Node.js.

·       Experience with Node.js / Express.

·       Basic React exposure for working with frontend teams or internal tools.

·       Exposure to Java / Spring Boot in enterprise application environments.

·       Experience with gRPC.

·       Experience with API gateways such as Azure API Management, Apigee, NGINX, or similar.

·       Experience with Infrastructure-as-Code tools such as Terraform.

·       Exposure to observability tools such as Prometheus, Grafana, Datadog, New Relic, Elastic APM, or similar.

·       Familiarity with OpenTelemetry for traces, metrics, and logs.

·       Exposure to Databricks, Spark, Delta Lake, or Unity Catalog.

·       Exposure to Azure Machine Learning or Google Vertex AI.

·       Prior exposure to LangChain, LangGraph, CrewAI, Semantic Kernel, or similar AI orchestration frameworks.

·       Exposure to vector databases, embeddings, RAG pipelines, or LLM APIs.

Summary

This role is suitable for a strong 4–5 year Python backend developer who wants to move into AI engineering. The candidate should already be capable of building reliable backend services, APIs, integrations, and database-backed applications. Through structured bridge training, the candidate will be enabled to work on enterprise AI applications involving LLMs, RAG, agents, orchestration frameworks, and AI observability.