Senior Software Engineer

Company Description

We are building an intelligence engine layer for AI agents.

As more companies adopt AI agents, the real challenge is no longer only generatingactions or automating workflows. The challenge is helping agents understand how a business actually works: its entities, processes, decisions, context, communication, operational state, and changing reality.

Synora turns fragmented business data, communication, workflows, and system signals into a structured intelligence layer that AI agents can reason over and act upon. We are building a data-oriented, AI-native platform that connects unstructured and structured information, models business context, and enables agents to make better, more reliable, and explainable decisions.

This is an early-stage startup, so we are looking for engineers who can move fast, think deeply, and own real production systems end to end.

Role Description

We are looking for a Senior Software Engineer to help design, build, and deliver the core Synora product.

This role is for someone who can take a complex requirement, understand the product and data context, ask the right questions, design the right architecture, implement it and bring it to production.

You will work on systems involving AI-native workflows, data pipelines, APIs, cloud infrastructure, databases, orchestration, monitoring, and production-grade backend services.

We are building with modern AI-assisted engineering practices: AI coding tools, agentic development, context engineering, fast iteration, and strong human engineering judgment.

What You’ll Do

• Design and build core backend services, data flows, and product capabilities.
• Deliver features end to end, from requirement clarification to production.
• Build AI-native and data-oriented systems that power agent intelligence.
• Develop scalable APIs, pipelines, integrations, and infrastructure components.
• Design for reliability, observability, performance, and maintainability.
• Use modern AI development tools to accelerate delivery while keeping high engineering standards.
• Collaborate closely with product, leadership, and engineering to shape the system and architecture.

What We’re Looking For

• A strong backend engineer with production experience and architectural thinking.
• Someone who can own complex features end to end in a small startup team.
• Strong understanding of cloud, infrastructure, databases, distributed systems, and production-grade application logic.
• Data-oriented mindset: modeling, pipelines, performance, consistency, and scale.
• Ability to work with ambiguity, ask sharp questions, and turn vague ideas into working systems.
• Comfortable using AI coding tools, agents, and modern productivity workflows.
• High ownership, strong communication, and good engineering judgment.

Experience & Background

• Strong professional backend engineering experience, typically 5+ years.
• Proven ability to design, build, and operate production systems.
• Experience delivering complex features end to end, not only isolated tickets.
• Experience designing services, data models, APIs, and scalable backend architectures.
• Experience with cloud platforms such as GCP, AWS, or Azure.
• Experience with databases such as PostgreSQL, Redis, Neo4j, or similar.
• Experience with monitoring, logging, debugging, performance optimization, and production operations.
• Experience with continuous delivery, distributed systems, and modern engineering workflows.
• We care more about ownership, production exposure, and technical depth than formal years of experience.
• Experience in early-stage startups or high-ownership environments is highly valued.

Strong Advantages

• Experience with AI-native systems, AI agents, LLM-based products, or agent orchestration.
• Experience with event-driven architecture, Kafka, Pub/Sub, queues, or streaming systems.
• Experience with data pipelines, workflow engines, or orchestration systems.
• Experience with Kubernetes, Docker, Terraform, Helm, or cloud-native infrastructure.
• Experience with graph databases, search engines, knowledge graphs, or semantic data models.
• Experience with observability tools such as Grafana, Prometheus, OpenTelemetry, or Cloud Monitoring.
• Experience using tools like Cursor, Claude Code, Codex, or similar AI-assisted development environments.

AI-Native Engineering Mindset

We believe AI can make strong engineers dramatically more productive, but it does not replace engineering judgment.

We expect engineers to know how to use AI tools effectively: provide context, ask the right questions, reverse-prompt unclear requirements, explore implementation options, review generated code, detect shortcuts, and turn AI-assisted output into reliable production software.

This role is not just about writing code faster. It is about building better systems faster.

Why Join Us

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 problem: building the intelligence layer that allows AI agents to understand businesses, reason over real operational 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.