Job Role: AI Developer Location: Remote
JD: Core Responsibilities - Design develop and deploy autonomous AI agents using frameworks like LangChain or LlamaIndex.
- Implement agent reasoning planning and tool use for executing real-world multi-step workflows.
- Integrate memory systems and RAG (Retrieval-Augmented Generation) using vector databases for context management.
- Ensure agent reliability safety and governance by establishing robust guardrails and error handling.
- Collaborate with product teams to translate complex business needs into agent-based automation solutions.
- Monitor scale and maintain deployed agents as production microservices on cloud platforms.
Key Technical Skills - Expertise in Python and modern software development practices.
- Hands-on experience with Large Language Models (LLMs) and advanced prompt engineering.
- Familiarity with containerization (Docker/Kubernetes) and CI/CD pipelines.
- Knowledge of cloud infrastructure (AWS Azure or GCP) for AI service deployment.
Job Role: AI Developer Location: Remote JD: Core Responsibilities Design develop and deploy autonomous AI agents using frameworks like LangChain or LlamaIndex. Implement agent reasoning planning and tool use for executing real-world multi-step workflows. Integrate memory systems and RA...
Job Role: AI Developer Location: Remote
JD: Core Responsibilities - Design develop and deploy autonomous AI agents using frameworks like LangChain or LlamaIndex.
- Implement agent reasoning planning and tool use for executing real-world multi-step workflows.
- Integrate memory systems and RAG (Retrieval-Augmented Generation) using vector databases for context management.
- Ensure agent reliability safety and governance by establishing robust guardrails and error handling.
- Collaborate with product teams to translate complex business needs into agent-based automation solutions.
- Monitor scale and maintain deployed agents as production microservices on cloud platforms.
Key Technical Skills - Expertise in Python and modern software development practices.
- Hands-on experience with Large Language Models (LLMs) and advanced prompt engineering.
- Familiarity with containerization (Docker/Kubernetes) and CI/CD pipelines.
- Knowledge of cloud infrastructure (AWS Azure or GCP) for AI service deployment.
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