Senior Software Engineer - Agentic AI & Data-Driven Systems

axion.com

San Francisco (CA)

Presencial

USD 180.000 - 240.000

Jornada completa

Hace 10 días

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

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Ventajas ofrecidas por este puesto de trabajo

Medical/Dental/Vision
HSA Plan
Unlimited PTO
401(k) Plan
Perks & Benefits

Descripción de la vacante

Axion in San Francisco is seeking an experienced Software Engineer to architect and scale the agentic systems at the heart of the Axion platform. You will own design decisions shaping how our agents reason, act, and integrate with enterprise data, collaborating with Engineering and Product leadership on high-stakes outcomes.

The role focuses on building reliable, data-intensive, non-deterministic AI systems and maintaining rigorous evaluation, observability, and guardrails to prevent errors in

Formación

  • Experience building agentic systems and LLM orchestration.
  • Design and own complex distributed data-intensive SaaS systems.
  • Fluency with non-deterministic, LLM-driven system reliability.

Responsabilidades

  • Own technical architecture for agentic systems and guardrails.
  • Hardening the reasoning layer and data ingestion pipelines at scale.
  • Establish evaluation and observability for non-deterministic AI.
  • Mentor engineers on agentic patterns and system design.

Conocimientos

Agentic systems
LLM orchestration
Multi-step reasoning
Multi-agent reasoning
Retrieval & context engineering
Interoperability protocols (MCP)

Herramientas

MCP

Descripción del empleo

Axion in San Francisco is seeking an experienced Software Engineer to architect and scale the agentic systems at the heart of the Axion platform. You will own design decisions shaping how our agents reason, act, and integrate with enterprise data, collaborating with Engineering and Product leadership on high-stakes outcomes.

The role focuses on building reliable, data-intensive, non-deterministic AI systems and maintaining rigorous evaluation, observability, and guardrails to prevent errors in

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