Python Developers

Python Developer (AI Integration Focus)Junior(4-7 years)Senior(8-12 years)Role OverviewSupport development and integration of Gen AI-enabled services, including LLM integrations and emerging agent-based workflows. Work under senior guidance to build scalable APIs and automation components in a cloud-based enterprise environment.Design and build scalable, enterprise-grade systems integrating GenAI and agentic orchestration frameworks into core business platforms. Lead the development of multi-agent workflows, real-time integrations, and cloud-native architectures, enabling intelligent automation and AI-driven enterprise applications.Key ResponsibilitiesDevelop Python-based APIs and backend servicesIntegrate LLM APIs into applicationsDesign and refine prompts for LLM-based applicationsSupport development of simple AI workflows using leading IDEs (VS Code, Cursor, Pycharm)Assist in deployment on AzureSupport integration with core systems and workflow platformsDebug, test, and optimize application componentsMaintain documentation and technical specificationsExperience in using coding agents (GitHub copilot, Cursor etc)Architecture and EngineeringArchitect and develop Python-based microservices for GenAI and enterprise platformsDesign and implement cloud-native and serverless architectures (Azure/AWS)Build scalable APIs and backend systems for high-performance enterprise environments Deploy, manage, and optimize services in cloud environments Agentic AI & OrchestrationDesign and implement agentic workflows and orchestration layers Build multi-agent systems and AI orchestration services Implement Agent-to-Agent (A2A) integration patterns Design agent registries and service discovery frameworks Enable tool-calling frameworks within LLM-driven workflows RAG & AI PipelinesDesign, implement, and manage: RAG pipelines and architectures Embedding workflows Real-time document processing pipelines Optimize retrieval accuracy and pipeline performance Enterprise IntegrationIntegrate AI systems with enterprise platforms using: MCP connectors (Model Context Protocol or equivalent) APIs, middleware, and event-driven integrations Ensure high scalability, resilience, and fault tolerance Performance & OperationsOptimize message handling and high-volume system interactions Implement logging, monitoring, and security controls Ensure production readiness and operational excellence Collaboration & LeadershipCollaborate with business stakeholders, architects, and AI teams Mentor junior engineers and guide technical design decisionsTechnical RequirementsStrong fundamentals in PythonExperience building REST APIsFamiliarity with:FastAPI / Flask / DjangoJSON, async programming basicsBasic understanding of:LLM APIs (Azure OpenAI or equivalent)Prompt-based integrationsPrompt EngineeringExposure to:Git and CI/CD pipelinesAzure cloud fundamentalsBasic database knowledge (SQL / NoSQL)Core EngineeringAdvanced proficiency in Python Strong experience in: FastAPI / Django Async programming Event-driven architectures Microservices design Experience with: Azure/AWS cloud services Containerization (Docker, Kubernetes) API management / gateway design AI & Agentic CapabilitiesStrong understanding of: LLM ecosystems (Claude, GPT, Gemini) LLM integration patterns Prompt engineering (few-shot, structured prompting, chaining) Tool invocation frameworks Experience with: Agentic frameworks and orchestration Workflow coordination across multiple AI services RAG architectures and patterns Vector databases Familiarity with: MCP connectors or contextual integration frameworks Enterprise IntegrationExperience integrating AI layers with legacy enterprise systems Strong understanding of: API scalability Distributed system resilience High-availability architecturesPreferred QualificationsExposure to GenAI projects Basic understanding of multi-step AI workflowsFamiliarity with containerization (Docker – basic level)Strong communication skillsOptional: Exposure to insurance domain (Claims / UW) is a plusProven experience implementing agentic AI systems in production Strong prompt engineering expertise Exposure to Responsible AI frameworks and governance Experience working with distributed/global engineering teams Strong stakeholder communication skills Domain experience: Insurance – Claims / Underwriting systems is a plusOriginally posted on Himalayas