About Us
Argoman is a venture studio focused on building AI-driven products and startups. We operate like a startup factory — identifying high-potential ideas, validating them through research and experimentation, and turning them into scalable businesses. Our team combines innovation, technology, and business insight to create real-world solutions powered by artificial intelligence. At Argoman, you’ll be part of a dynamic and collaborative environment where ideas grow into products, and products evolve into independent companies.


What You’ll Do
As a Technical Software Engineer, you’ll collaborate with cross-functional squads to design, build, and maintain AI-driven applications and internal monitoring systems. You’ll take a hands-on role in ensuring our technology remains reliable, performant, and scalable as we innovate and expand.

Your responsibilities will include:
- Designing, developing, and maintaining robust backend services using Python.
- Monitoring the health, performance, and uptime of AI-based systems across multiple projects.
- Building internal tools and dashboards to track key system metrics, logs, and usage analytics.
- Writing clean, efficient, and testable code for both experimental and production-grade systems.
- Collaborating closely with data engineers, product managers, and founders across different squads.
- Contributing to the architecture, design, and implementation of APIs and microservices.
- Supporting deployments, diagnosing production issues, and improving overall system observability.
- Helping define and uphold best practices for CI/CD, infrastructure automation, and quality assurance.

What We’re Looking For
Required Skills & Experience
- Strong programming skills in Python.
- Solid understanding of Docker and containerized application development.
- Proficiency with frameworks such as FastAPI and Django.
- Experience with system monitoring, logging, and alerting tools (e.g., Prometheus, Grafana, Sentry, Datadog).
- A product-oriented mindset — you think beyond code, focusing on usability, scalability, and business value.
- Experience with task queues and asynchronous architectures (Celery, RabbitMQ, Redis, etc.).

Nice to Have
- Hands-on experience with AI/ML pipelines or LLM-based systems.
- Previous experience in a startup or venture studio environment.