Senior AI Backend Engineer - Onsite SF

Jeeva AI

San Francisco (CA)

Sur place

USD 130 000 - 180 000

Plein temps

14 jours+
Générateur de candidature

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Avantages offerts par ce poste

Equity: Competitive
Medical, dental, vision insurance
Paid time off

Résumé du poste

Jeeva AI is seeking a Sr. AI Backend Engineer to join the Agentic Platform team in San Francisco. You will design, develop, and deploy intelligent AI agents and multi-agent systems powering Jeeva’s core product.

This senior IC role requires a minimum of 5 years of relevant experience and deep expertise in LLMs and agentic workflows. You will collaborate with data scientists, product managers, and engineers to deliver scalable backend features, leveraging containerized deployments on

Qualifications

  • Minimum 5 years of backend/AI engineering experience.
  • Strong knowledge of LLMs, retrieval-augmented generation (RAG), and agentic workflows.
  • Ability to design scalable, production-grade backend services.

Responsabilités

  • Design, develop, and deploy AI agents and multi-agent systems for production environments.
  • Build and optimize applications using LLMs (GPT, T5, BERT) and transformer architectures.
  • Implement RAG frameworks to improve agent accuracy and context-awareness.
  • Develop agent pipelines using LangChain, OpenAI Gym, Rasa, Ray RLlib, or equivalents.
  • Collaborate with data scientists, product managers, and engineers to deliver features.

Connaissances

Python
LLMs
Multi-agent systems
RAG
LangChain
API development

Outils

Docker
Kubernetes
MongoDB
OpenAI Gym
Rasa
Ray RLlib

Description du poste

Jeeva AI is seeking a Sr. AI Backend Engineer to join the Agentic Platform team in San Francisco. You will design, develop, and deploy intelligent AI agents and multi-agent systems powering Jeeva’s core product.

This senior IC role requires a minimum of 5 years of relevant experience and deep expertise in LLMs and agentic workflows. You will collaborate with data scientists, product managers, and engineers to deliver scalable backend features, leveraging containerized deployments on

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