Software Engineer

AI-Native Platform Agentic Systems 6 - 12 Years Experience Startup Culture High Ownership

Role Overview

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We are building a next-generation AI-native platform and looking for engineers who are more than great coders, people who think in systems, take ownership end-to-end, and thrive in a fast-moving startup environment. This role sits at the intersection of software engineering, AI/ML tooling, cloud infrastructure, and security and you will be expected to work across all of them.

You will design and build production-grade software while actively leveraging AI coding agents (Claude, Codex, Ollama) to accelerate your workflow. Critically, you won’t just generate code, you’ll interrogate what the agents produce, understand the design decisions behind it, and ensure every output is correct, scalable, and maintainable.

What You’ll Do

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Design & Architecture

Translate ambiguous requirements into clear, well-reasoned technical designs

Make informed build-vs-reuse decisions considering scalability, cost, and maintainability

Define service boundaries, data models, and API contracts across distributed systems

Identify and proactively address technical debt before it compounds

AI-Augmented Development

Use coding agents (Claude, Codex, Ollama) as first-class tools to accelerate design, prototyping, and development

Critically evaluate agent-generated code for correctness, security, and alignment with system requirements

Understand and articulate why an agent made a specific design or coding choice not just what it produced

Build internal tooling and prompt patterns that improve team-wide leverage of AI coding tools

Contribute to best practices for human-AI collaborative development workflows

Engineering & Delivery

Write clean, tested, and well-documented code across Python, Go, and TypeScript/Node.js

Design and optimize data pipelines using TimescaleDB and caching layers (Redis, Memcached, etc.)

Own features end-to-end: from requirements through design, implementation, testing, and production monitoring

Conduct thorough code reviews with a focus on correctness, performance, and long-term maintainability

Debug complex issues spanning multiple services, layers, and infrastructure boundaries

Write meaningful unit, integration, and load tests; contribute to CI/CD pipeline improvements

Agentic AI & LLM Systems

Design and implement agentic AI workflows: tool use, multi-agent orchestration, memory, and retrieval

Integrate and fine-tune LLMs for specific platform use cases with robust evaluation pipelines

Build reliable inference infrastructure with appropriate observability, fallbacks, and cost controls

Stay current on fast-evolving AI/ML tooling and bring relevant capabilities into the platform

Infrastructure & Security

Deploy and operate services on Kubernetes across AWS, GKE, and Azure environments

Design secure-by-default systems: authentication, authorization, secrets management, network policies

Implement and maintain observability stacks (metrics, tracing, alerting) for production services

Apply networking fundamentals (DNS, TCP/IP, TLS, VPNs, load balancing) to real infrastructure problems

Who You Are

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Deep Thinker

You don’t just implement you understand. You ask why before how, and you push back on requirements that don’t make sense.

AI-Native Engineer

You actively use AI tools to work faster and smarter, and you know how to verify and improve what they produce.

Relentless Debugger

You chase bugs to their root cause and document what you find. You never accept ‘it works, don’t touch it.’

Systems Thinker

You consider edge cases, failure modes, and future extensibility naturally not as an afterthought.

Ownership Mindset

When you commit to something, it ships. You follow through, communicate proactively, and close the loop.

Startup DNA

You’re comfortable with ambiguity. You can context-switch, re-prioritize, and make good decisions with incomplete information.

Collaborative Builder

You give direct, constructive feedback in code reviews. You lift teammates rather than gatekeep knowledge.

Technical Skills

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Core Languages

Python Services, ML pipelines, scripting

Go (Golang) high-performance backends, CLIs

TypeScript / Node.js — APIs, frontend tooling

SQL — complex queries, schema design

Data & Caching

TimescaleDB — time-series data modeling & queries

PostgreSQL — relati…