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Job details:
AI Agentic Developer
Location: Remote
Experience: 2–5 years
Employment Type: Full-time
About the Role
We're looking for an AI Agentic Developer to design, build, and deploy autonomous and semi-autonomous AI agents that can plan, reason, and take actions across tools, APIs, and workflows. You'll work at the intersection of LLM engineering, backend systems, and product turning agentic AI concepts into reliable, production-grade features.
What You'll Do
• Design and build AI agents using frameworks like LangChain, LangGraph, CrewAI, AutoGen, or custom orchestration layers
• Integrate LLMs (OpenAI, Anthropic Claude, open-source models) into agentic workflows with tool-calling, function-calling, and multi-step reasoning
• Build and maintain the infrastructure that lets agents interact with APIs, databases, and third-party services (e.g., webhooks, MCP servers, RAG pipelines)
• Implement memory, context management, and state persistence for long-running agents
• Design prompt strategies, evaluation harnesses, and guardrails to keep agent behavior reliable and safe
• Collaborate with backend/frontend engineers to ship agent-powered features into production
• Monitor, debug, and iterate on agent performance (latency, cost, accuracy, hallucination rate)
• Stay current with the fast-moving agentic AI ecosystem and bring in new techniques where useful
Required Skills
• Strong Python (or Node/TypeScript) backend development experience
• Hands-on experience with LLM APIs (OpenAI, Anthropic, etc.) and prompt/function-calling design
• Familiarity with agent frameworks (LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar)
• Understanding of RAG (retrieval-augmented generation), vector databases (Pinecone, Weaviate, Chroma, pgvector), and embeddings
• Experience with REST/webhook-based integrations and async task handling
• Solid grasp of API design, databases (SQL/NoSQL), and version control (Git)
• Ability to reason about agent safety, cost control, and failure modes
Nice to Have
• Experience with MCP (Model Context Protocol) or building tool-calling servers
• Familiarity with fine-tuning or evaluation frameworks for LLMs
• Experience deploying agents in production (AWS/VPS)
• Background in building multi-agent systems or workflow automation platforms
• Frontend skills (React/TypeScript) to help ship end-to-end agent experiences
• Knowledge of trading/financial markets — familiarity with concepts like technical indicators, alerts (e.g. TradingView/PineScript), or broker/exchange APIs is a plus
• Experience working with webhook-based alert/event systems and broker or trading platform integrations
Note: This is completely Remote Job. You must have your own laptop to work on.
Click on Apply to know more.
