Python Backend Developer
Altius Technologies Inc
- New York, New York, United States
- New York, New York, United States
About
4+ years of software development experience with production systems
Strong proficiency in Python and/or TypeScript/Node.js
Deep experience with REST APIs, GraphQL, and various integration patterns
Understanding of JSON-RPC, WebSocket, or similar RPC protocols
Expertise in async/await patterns and concurrent programming
Experience with authentication mechanisms (OAuth 2.0, JWT, API keys)
Strong grasp of error handling, logging, and observability practices
Experience building SDKs, libraries, or developer tools
Knowledge of security best practices for API integrations and data handling
Familiarity with Git, CI/CD pipelines, and deployment automation
Preferred Qualifications
Hands‑on experience with Model Context Protocol (MCP) specification and implementations
Experience integrating with LLM APIs (OpenAI, Anthropic, Azure OpenAI, Google Vertex AI)
Understanding of AI agent frameworks (FastMCP)
Knowledge of prompt engineering and LLM tool calling mechanisms
Experience with function calling and structured output from LLMs
Familiarity with enterprise platforms (Splunk, Databricks, Zendesk, Salesforce, Jira)
Understanding of token optimization and context window management
Experience with schema validation (JSON Schema, Pydantic, Zod)
Knowledge of containerization (Docker) and orchestration (Kubernetes)
Background in observability tools (Prometheus, Grafana, Datadog)
Contributions to open‑source AI/LLM projects
Technical Skills
Protocols: JSON-RPC 2.0, REST, GraphQL, Server‑Sent Events (SSE), WebSockets
Data: JSON Schema, Pydantic models, data validation and serialization
Domain Knowledge
Understanding of AI agent architectures and multi‑agent systems
Knowledge of LLM capabilities, limitations, and token economics
Familiarity with prompt engineering and context optimization techniques
Understanding of streaming responses and real‑time data handling
Experience with callback mechanisms and event‑driven architectures
Knowledge of data encryption and PII handling in AI contexts
Soft Skills
Strong problem‑solving ability with complex integration challenges
Excellent written communication for documentation and tool descriptions
Ability to design intuitive tool interfaces that LLMs can effectively use
Collaborative mindset for working with AI engineers and product teams
Attention to detail for schema design and error handling
Proactive approach to monitoring and improving connector reliability
Adaptability to rapidly evolving LLM and AI agent ecosystems
Day‑to‑Day Activities
Develop new MCP connectors for enterprise system integrations
Debug tool calling issues and optimize parameter handling for LLM consumption
Review and improve tool descriptions for better LLM understanding
Implement rate limiting and error handling for production robustness
Write unit tests and integration tests for connector reliability
Monitor connector performance and troubleshoot agent workflow failures
Collaborate with teams on new integration requirements
Update connectors as upstream APIs change or LLM capabilities expand
What You’ll Build
MCP servers exposing enterprise data and capabilities to AI agents
Tool schemas and validation logic for safe LLM interactions
Authentication and authorization layers for secure integrations
Retry mechanisms and error recovery for resilient agent workflows
Documentation and examples for connector usage
Testing frameworks ensuring reliability across LLM interactions
Monitoring and observability instrumentation for production systems
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Languages
- English
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