Software Engineer (Mid+)

About Actaware

Actaware is an AI startup building a deterministic, auditable intelligence platform that transforms millions of unstructured documents - PDFs, filings, reports, earnings calls - into decision-grade insights for investment managers and enterprises. Our stack powers explainable LLM pipelines, dynamic ontologies, and agentic document processing at scale, serving clients across financial markets and the public sector.

We're a small, sharp team of engineers, data scientists, and domain experts who ship fast and solve hard problems. If you want to work at the intersection of AI, data infrastructure, and high-stakes decision-making - this is the place.

The Role

We're looking for a Software Engineer who can own features end-to-end - from designing cloud infrastructure to shipping production ML pipelines. You'll work across the full stack of our platform: building scalable services, automating deployments, and integrating AI/ML components into a product that real customers depend on daily.

This is not a ticket-punching role. We need someone who sees a problem, figures out the best path forward, and executes - without waiting to be told what to do.

What You'll Work On

• Designing and building backend services and data pipelines in Python
• Deploying and managing infrastructure on AWS and/or Azure (Lambda, SQS, SNS, Athena, and more)
• Building and maintaining CI/CD pipelines using GitHub Actions
• Containerizing and orchestrating services with Docker and Kubernetes
• Integrating ML/AI models into production workflows (LLMs, NLP, agentic pipelines)
• Working with MongoDB and SQL databases to store and query structured and unstructured data
• Rapid prototyping and building MVPs to validate ideas and ship early versions fast
• Shaping and evolving core platform solutions - you'll have a direct impact on architecture and product direction
• Collaborating directly with data scientists, product, and leadership to ship features that matter

Recruitment Process

1. Application Review - we review your CV and intro
2. Technical Task - a take-home assignment to see how you approach real problems
3. Technical Screening - a conversation focused on your engineering skills, system design thinking, and experience
4. Final Interview - a meeting with the CTO and CEO to discuss culture fit, vision, and mutual expectations

How to Apply

Send your CV and a brief note about why this role interests you to job@actaware.com.

No cover letter template needed - just tell us what you've built and what excites you about Actaware.

Codzienne zadania

• Designing and building backend services and data pipelines in Python
• Deploying and managing infrastructure on AWS and/or Azure (Lambda, SQS, SNS, Athena, and more)
• Building and maintaining CI/CD pipelines using GitHub Actions
• Containerizing and orchestrating services with Docker and Kubernetes
• Integrating ML/AI models into production workflows (LLMs, NLP, agentic pipelines)
• Working with MongoDB and SQL databases to store and query structured and unstructured data
• Rapid prototyping and building MVPs to validate ideas and ship early versions fast
• Shaping and evolving core platform solutions - you'll have a direct impact on architecture and product direction
• Collaborating directly with data scientists, product, and leadership to ship features that matter

What We're Looking For

Technical skills:

• Mid+ level engineer with 3+ years of professional experience - we're looking for someone who can independently drive technical decisions and own their work end-to-end
• Strong proficiency in Python
• Hands-on experience with AWS and/or Azure cloud services (Lambda, SQS, SNS, Athena or equivalents)
• Solid understanding of CI/CD - you've built and maintained pipelines in GitHub Actions
• Production experience with Docker and Kubernetes
• Working knowledge of MongoDB and relational databases (SQL)
• Familiarity with ML/AI concepts and deploying models or LLM-based systems in production

Mindset:

• Critical thinker - you question assumptions and dig into root causes, not just symptoms
• Problem-solver by default - you focus on outcomes, not blockers
• Self-driven - you don't need hand-holding; you take ownership and figure things out
• Comfortable in a startup environment where priorities shift and ambiguity is normal

Must have

• Python
• Azure