Join our team

At Bloomteq, we know that exceptional organizations are built by exceptional people. That’s why we are always open to connecting with individuals who are curious, motivated, and eager to grow. We operate at the intersection of technology, innovation, and research, in an environment where collaboration, ownership, and continuous learning are part of everyday work. If you are passionate about creating meaningful solutions, developing your skills, and working alongside people who support and challenge each other, you might be a great fit for our team. Submitting an open application is an opportunity to introduce yourself, share your experience and interests, and tell us how you see your potential contribution. When a suitable opportunity arises, we will be happy to reconnect with you.

About the role

You'll build agentic AI systems that do real work—not demos. That means designing agents that plan, call tools, handle failures, and produce output a business can actually depend on.

We're moving toward AI-centric engineering across the company, and this role sits at the centre of it. You'll have real influence over how we build with these tools, what we standardize on, and where the line sits between what an agent should handle and what still needs a human.

What you'll work on

• Designing, building, and shipping agentic systems and LLM-powered workflows in Python.
• Working with LangChain and similar frameworks to orchestrate multi-step agent behaviour.
• Prompt design, tool and function calling, and retrieval pipelines using RAG.
• Evaluating agent performance by building the tests and metrics that determine whether it actually works.
• Integrating models and agents into production services and existing product workflows.
• Properly handling the unglamorous parts: cost, latency, failure modes, guardrails, and observability.
• Working with engineering and product teams to identify where this technology genuinely helps—and saying so when it doesn't.

What you need

• 3+ years of software development experience with Python.
• Hands-on experience building with LLMs and agentic frameworks such as LangChain or an equivalent—with something that reached production.
• An understanding of RAG, embeddings, vector stores such as Qdrant or Pinecone, and retrieval design.
• Experience treating prompt engineering and tool calling as engineering problems rather than experiments.
• The ability to evaluate LLM output systematically rather than by impression.
• Comfort integrating with REST APIs and cloud services.
• Strong ownership, communication, and problem-solving skills.

Strong advantages

Experience with any of the following is a strong advantage:

• LangGraph
• LlamaIndex
• Vector databases such as Qdrant, Pinecone, Weaviate, or pgvector
• AWS services such as Bedrock, Lambda, or SageMaker
• MLOps and model deployment
• A classical machine-learning background
• Fintech or payments
• Docker

Don't meet every requirement? Apply anyway. Nobody in this field does.

What matters most to us

We're not looking for someone who's built a chatbot demo.

We want an engineer who understands where these systems break, builds the evaluation that catches those failures, and can tell the difference between an agent that looks impressive and one that can be trusted in production.

About the role

We're rebuilding a proven gym and fitness management platform for a leader in the industry.

This is a live migration and modernization effort—not a greenfield project. The current system is established and working, and we're re-architecting and rebuilding it natively with modern practices, better performance, and long-term maintainability in mind.

This is a role for developers who are versatile across the mobile stack, think beyond the UI layer, and understand how their app fits into a larger service-oriented architecture.

What you'll do

• Design and build native mobile features in Swift/SwiftUI for iOS or Java/Kotlin for Android.
• Rebuild an established fitness and gym management platform using modern architecture.
• Work with backend teams to integrate services, APIs, and data flows into the mobile applications.
• Apply service-oriented and modular architecture principles to keep the codebase scalable.
• Write testable code and work with QA on coverage and quality practices.
• Use AI-assisted tools deliberately to improve productivity and code quality—not to paper over gaps in understanding.
• Investigate production issues and fix root causes rather than symptoms.
• Participate in Agile ceremonies and work closely with cross-functional teams.

What you need

• Solid commercial experience in native mobile development with Swift/SwiftUI or Java/Kotlin.
• Comfort with backend concepts, including APIs, services, data flows, and how a mobile application fits within a larger system.
• An understanding of service-oriented architecture and general software architecture principles.
• Awareness of QA practices and testing, including unit and integration testing, as well as a strong quality mindset.
• Hands-on experience using AI tools in daily development, with the judgment to know when to rely on them.
• A pragmatic, problem-solving mindset focused on root causes.
• Comfort working in an Agile, collaborative environment.

Strong advantages

• Experience with AWS, where the platform's backend services run.

Don't tick every box? Apply anyway.

A note on AI

We're moving toward AI-centric engineering practices.

We're not looking for people who avoid AI tools—or people who lean on them to mask what they don't actually know. We want engineers who use tools like Claude to genuinely raise the bar on their own work.

What matters most to us

We're not looking for someone to simply port screens across.

We want a developer who understands why the old system worked, makes deliberate decisions about what to keep and what to rebuild, and leaves behind an application that's still maintainable in three years.