Python Developer DevOps

About the Role:

We’re seeking a hands-on Software Engineer to join our team and take ownership of our python utilities, Generative AI Integration and innovation, CI/CD pipelines, container orchestration, and automation frameworks. In this role, you’ll build and maintain Python utilities, infrastructure using Azure DevOps, design and operate containerized environments (Docker, Kubernetes/k3s), author configuration management playbooks (Ansible, YAML), and develop Python scripts and applications to streamline our workflows. A working knowledge of Generative AI tools and their integration into development processes is also highly valued.

Key Responsibilities:

• 
  Python Development & Automation
• Design, develop, and maintain Python scripts, modules, and small services to automate routine tasks (log parsing, system health checks, notifications).
• Build custom integrations (e.g., API clients, CLI tools) to interface with cloud services, internal tools, or monitoring platforms.
• Ensure code quality by writing unit tests, adhering to PEP8 conventions, and leveraging continuous testing frameworks.

• 
  Generative AI Integration & Innovation

o Research and evaluate Gen AI tools/SDKs (e.g., OpenAI, Azure OpenAI, Hugging Face) for potential use cases: code generation, automated documentation, chatbots for internal support.

o Architect and implement a Retrieval-Augmented Generation (RAG) chatbot that can pull from internal knowledge bases (e.g., Confluence, Git repos, SharePoint) using embeddings and vector search.

o Select and configure a vector database (e.g., Azure Cognitive Search with vector support, Pinecone, or similar) and develop the pipeline to ingest, index, and periodically refresh documents.

o Build the middleware in Python (or Node.js) to handle user queries: embed the question, retrieve top-k relevant passages, and pass context into a large language model (OpenAI/Azure OpenAI) for answer generation.

o Prototype and proof-of-concept small Gen AI–driven automations (e.g., automated code reviews, intelligent alerts).

o Monitor usage, tune retrieval parameters (embedding model, similarity thresholds, chunk sizes), and measure response relevance (e.g., via feedback loops or metrics) to improve accuracy over time.

o Document the end-to-end RAG architecture, code components, and operational runbooks (indexing schedules, error handling, cost monitoring).

o Partner with data science or AI teams to integrate machine-learning pipelines into DevOps workflows when applicable.

• Azure DevOps Pipelines & Releases
• Automate build, test, and deployment workflows for microservices and infrastructure-as-code (IaC).
• Debug & Troubleshoot Failed Pipelines: When a deployment pipeline fails, investigate logs and error messages, reproduce the issue locally or in a test environment, identify root causes (e.g., misconfigurations, dependency errors, script failures), and work with developers to resolve the problem. Provide clear feedback—via comments in Azure DevOps or team channels—so that fixes can be applied rapidly.
• Monitor pipeline health (build durations, failure rates, flaky tests) and continuously improve pipeline reliability and performance.
• Containerization & Orchestration
• Containerize applications using Docker; author and maintain Dockerfiles and multi-stage builds.
• Deploy and manage Kubernetes clusters (up to production scale), including cluster provisioning, upgrades, and configuration.
• Operate lightweight Kubernetes distributions (k3s) for lower-resource or edge scenarios.
• Monitor cluster health, troubleshoot pod/container issues, and implement best practices for auto-scaling, networking, and storage.
• Configuration Management & Infrastructure as Code
• Develop and maintain Ansible playbooks, roles, and inventories to automate server provisioning, configuration, and application deployment.
• Write and manage YAML-based manifests for Kubernetes objects (Deployments, Services, ConfigMaps, Secrets, Ingresses).
• Collaborate to define and enforce infrastructure standards (naming conventions, tagging, resource sizing, security baselines).
• Collaboration & Knowledge Sharing
• Document processes, runbooks, and “how-to” guides (using Confluence, Markdown, etc.) for cross-team visibility.
• Lead or participate in architecture/design reviews, highlighting operational considerations and trade-offs.

Skills Required:

Azure DevOps (Pipelines, Repos, Artifacts), Python (3.x) ,AWX,

YAML, API development (RESTful APIs, Swagger/Open API), Grafana,

Docker OpenAI/Azure OpenAI (or equivalent Gen AI SDK), Azure Resource Manager (Virtual Networks, Storage Accounts, IAM),

Kubernetes (including k3s, K9s), Embedding models (e.g., OpenAI embeddings, Sentence Transformers) Zabbix (monitoring),

Helm Vector databases (e.g., Pinecone, Azure Cognitive Search), Azure Monitor,

Ansible, Terraform (or ARM Templates/Bicep) ETC.