Senior Python Backend Engineer – AI & Data Platform

Senior Python Backend Engineer – AI & Data PlatformAbout Synora

Synora is building an AI-native intelligence layer that helps AI agents understand how businesses actually work.

We connect fragmented business data, workflows, communication, operational signals, and system context into a structured layer that agents can reason over and act upon.

As more companies adopt AI agents, the challenge is no longer just automation — it is giving agents the right business context, state, and data foundation to make reliable and explainable decisions.

We are an early-stage startup looking for a strong hands-on engineer who wants to build core product infrastructure from the ground up.

We are looking for a Senior Python Backend Engineer to help design, build, and own key parts of Synora’s backend and data-oriented infrastructure.

You will work on production backend services, APIs, integrations, data flows, cloud infrastructure, databases, orchestration, monitoring, and AI-native product capabilities.

Build production-grade backend services and APIs in Python.

Design data flows, integrations, and infrastructure components that connect structured and unstructured business information.

Work on AI-native backend capabilities that support agent intelligence, reasoning, and reliable decision-making.

Own features end to end — from requirements and architecture to deployment, monitoring, and production support.

Build scalable, observable, and maintainable systems.

Work closely with product, leadership, and engineering to shape the system architecture and technical direction.

Use modern AI-assisted development tools while applying strong engineering judgment.

Strong hands-on experience building backend systems in Python in production.

Backend engineering experience with real ownership of production systems.

Experience designing and building APIs, services, data models, integrations, or distributed backend systems.

Strong understanding of cloud infrastructure, databases, performance, reliability, and production operations.

Data-oriented mindset: pipelines, modeling, consistency, scale, and maintainability.

Ability to work with ambiguity, ask sharp questions, and turn complex ideas into working systems.

High ownership, strong communication, and good engineering judgment.

Comfort working in a fast-moving early-stage startup environment.

Experience with AI-native systems, LLM-based products, RAG, AI agents, vector search, semantic search, or agent orchestration.

Experience with data pipelines, workflow engines, ETL/ELT, CDC, or event-driven systems.

Experience with queues or streaming technologies such as Kafka, RabbitMQ, Pub/Sub, SQS/SNS, or Celery.

Experience with Kubernetes, Docker, Terraform, Helm, or cloud-native infrastructure.

Experience with PostgreSQL, Redis, BigQuery, ClickHouse, MongoDB, graph databases, vector databases, or search engines.

Experience with observability tools such as Grafana, Prometheus, OpenTelemetry, Cloud Monitoring, or similar.

Experience using AI-assisted development tools such as Cursor, Claude Code, Codex, or similar.

You will join at an early stage and help shape the core product, architecture, engineering culture, and technical direction.

You will work on a meaningful infrastructure problem: building the intelligence layer that allows AI agents to understand real business context and act with greater reliability.

This is a role for someone who wants ownership, impact, and the opportunity to build a foundational AI infrastructure product from the ground up.

If this feels like the kind of problem you want to help solve, we’d love to hear from you!