Senior Python Backend Engineer - Durable AI Orchestration

BairesDev; Chile; A distancia; CLP 117.417.000 - 176.125.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

100% remote work

Flexible hours

Home office setup

Competitive compensation in USD

Descripción de la vacante

BairesDev is seeking a Senior Python Backend Engineer to join a fully remote team. You will help build the control plane of a system that writes its own code, orchestrates durable workflows, and coordinates AI models with strict governance and auditability.

You will design PostgreSQL data models for run state and provenance, implement workflows with Temporal, and develop agent adapters while ensuring security and scalable performance.

Formación

• 8+ years in backend software engineering.
• Strong Python proficiency; Go acceptable as a secondary language.
• Experience with durable workflow orchestration (Temporal or equivalents).
• Experience with agentic systems and tool mediation.
• Background in context engineering and code retrieval tools.
• Proficient in PostgreSQL data modeling.
• Advanced English required.

Responsabilidades

• Build the harness control plane and backend services using Python.
• Implement durable workflow orchestration using Temporal.
• Build agent adapters and tool mediation via MCP gateway.
• Compile minimal context using structural code retrieval.
• Design PostgreSQL data models for run state, policy versions, provenance chains.

Conocimientos

Python

Go

Temporal

Agentic system

Context engineering

PostgreSQL

English

Herramientas

Cadence

Camunda

Step Functions

Tree-sitter

Language servers

ripgrep

Git

OpenTelemetry

Langfuse

LangChain/LangGraph

Descripción del empleo

BairesDev is seeking a Senior Python Backend Engineer to join a fully remote team. You will help build the control plane of a system that writes its own code, orchestrates durable workflows, and coordinates AI models with strict governance and auditability.

You will design PostgreSQL data models for run state and provenance, implement workflows with Temporal, and develop agent adapters while ensuring security and scalable performance.