Tasks:
- * Deliver knowledge transfer to internal teams
- * Design and develop AI agents and multi-agent workflows
- * Develop synchronous and asynchronous Python backend services
- * Document technical designs, integrations, and operational guidance
- * Implement identity, authentication, authorization, and secrets management
- * Implement prompts, tools, and agent execution logic
- * Implement RAG, embeddings, semantic search, and context management
- * Instrument logs, traces, metrics, token usage, and agent monitoring
- * Integrate agents with Azure AI Foundry and AWS Bedrock
- * Integrate enterprise tools and services through REST APIs, MCP, and APIM
- * Integrate LLMs through gateways, including routing and fallback
- * Test agent functionality, quality, accuracy, regression, and error handling
- * Version agents, prompts, and configurations across DEV, QA, and PROD
Perks/Benefits:
Skills/Tech stack required:
[Agentic AI] [Agent Orchestration] [AI Foundry] [API Management APIM] [Asynchronous programming] [Authentication and Authorization] [AWS Bedrock] [Azure AI] [Azure AI Foundry] [Azure API] [Azure API Management] [Azure API Management (APIM)] [CI/CD] [Cloud Integration] [CrewAI] [Embeddings] [Event Driven] [Event Driven Programming] [Function Calling] [Generative AI] [Git] [Grounding] [Langchain] [Langgraph] [Language Models (LLMs)] [Large Language Models] [Large Language Models (LLMs)] [LLM Evaluation] [LLM gateways] [Model Context Protocol] [Model Context Protocol MCP] [Multi-Agent] [Multi-agent orchestration] [Observability] [Prompt engineering] [Protocol MCP] [Python] [REST APIs] [Retrieval-Augmented Generation] [Retrieval-Augmented Generation RAG] [Secrets management] [Semantic Search] [Tool-Calling] [Vector Search]
Educational requirements:
N/A
Role(s):
[Agent Developer] [AI Agent Developer] [AI Engineer] [Backend Developer] [Developer] [Engineer] [Generative AI Engineer]