Job description
Python Developer (AI Integration Focus)
Junior(4-7 years)
Senior(8-12 years)
Role Overview
Support 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 Responsibilities
Develop Python-based APIs and backend services
Integrate LLM APIs into applications
Design and refine prompts for LLM-based applications
Support development of simple AI workflows using leading IDEs (VS Code, Cursor, Pycharm)
Assist in deployment on Azure
Support integration with core systems and workflow platforms
Debug, test, and optimize application components
Maintain documentation and technical specifications
Experience in using coding agents (GitHub copilot, Cursor etc)
Architecture and Engineering
Architect and develop Python-based microservices for GenAI and enterprise platforms
Design 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 & Orchestration
Design 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 Pipelines
Design, implement, and manage:
RAG pipelines and architectures
Embedding workflows
Real-time document processing pipelines
Optimize retrieval accuracy and pipeline performance
Enterprise Integration
Integrate 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 & Operations
Optimize message handling and high-volume system interactions
Implement logging, monitoring, and security controls
Ensure production readiness and operational excellence
Collaboration & Leadership
Collaborate with business stakeholders, architects, and AI teams
Mentor junior engineers and guide technical design decisions
Technical Requirements
Strong fundamentals in Python
Experience building REST APIs
Familiarity with:
FastAPI / Flask / Django
JSON, async programming basics
Basic understanding of:
LLM APIs (Azure OpenAI or equivalent)
Prompt-based integrations
Prompt Engineering
Exposure to:
Git and CI/CD pipelines
Azure cloud fundamentals
Basic database knowledge (SQL / NoSQL)
Core Engineering
Advanced 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 Capabilities
Strong 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 Integration
Experience integrating AI layers with legacy enterprise systems
Strong understanding of:
API scalability
Distributed system resilience
High-availability architectures
Preferred Qualifications
Exposure to GenAI projects
Basic understanding of multi-step AI workflows
Familiarity with containerization (Docker – basic level)
Strong communication skills
Optional: Exposure to insurance domain (Claims / UW) is a plus
Proven 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 plus
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.