What we are building

Mimica is an AI-powered process intelligence platform enabling enterprises and individuals to reclaim their most precious resource: time. We've all seen repetitive tasks and redundant processes quietly drain productivity and creativity. Not because companies don’t want to become more efficient, but because they don’t know where to start.

Mimica automatically analyzes your team’s work, then generates the AI agents to execute it. Our software turns everyday work into data-backed decisions, helping companies remove process bottlenecks, automate the right tasks, and upskill teams with precision and confidence.

We’ve raised $26 million in Series B financing and are scaling fast. Backed by investors including Khosla Ventures and Paladin Capital, our proprietary AI technology is trusted by Fortune 500 companies to accelerate transformation. Mimica is recognized as a Top 100 AI Start-up by Accel and an industry Leader by the Everest Group.

Our team

Behind our platform is a team of exceptionally talented people, remote-first and globally distributed across 16+ countries. We're looking for curious, collaborative people excited to solve complex problems. You'll join a fast-paced environment built on high ownership, bottom-up thinking, and transparent, open communication – helping some of the world's leading organizations transform the way work gets done with AI.

Where we are in our scale-up journey

We’ve achieved strong product-market fit and are now scaling with intention. You’ll join a 50+ person team of Senior+ engineers and Product leaders who prioritise product impact over mere headcount. We have 8 cross-functional teams, including a dedicated Platform team focused on infra & developer experience. We started building proprietary ML before the LLM boom, so we don't just consume models - we train them from the ground up.

Our approach to engineering

We prioritise customer needs first

We work in small, project-based teams

We have flexibility in terms of the problems we work on

We own the full lifecycle of our projects

We avoid silos and encourage taking up tasks in new areas

We balance quality and velocity

We have a shared responsibility for our production code

We each set our own routine to maximise our productivity

What will you own

In this role, you will own and support the development of backend systems that interface with ML models. You will build apps and core components of our ML systems, deliver new AI features and drive improvements to our infrastructure and services.

We are currently looking for Engineers to join one of our teams:

Maker Team, a team responsible for building out the automation engine, as one of its founding members. We're building a new product from scratch, and that means being a part of the design of its architecture, experimentation, and development.

Data Intelligence Team, whose goal is to provide ML-enriched data for downstream tasks and ensure user data privacy. You will support our data orchestration and processing pipeline, as we build with scalability in mind.

In all cases, we're looking for a Lead/Staff-level engineer to join the Python Chapter, who will have the opportunity to shape our technical direction, architecture, processes, and culture, and to level up the team and Chapter in development practices.

What you will be doing

Write Python applications that are resilient, robust, and integrate well with other apps in a service architecture.

Furthering Developer Experience (DevEx) by mentoring others in writing code that is intuitive, clear, and easy to test

Developing observability for new and existing ML applications and GenAI/LLM integrations, making use of the Grafana Stack (Prometheus, Loki, Tempo)

Develop integrations and services that communicate with Google Services.

Working closely with Data Scientists and ML Engineers throughout the lifecycle of productionising their models

Being responsive to incidents regarding ML applications - including an understanding of how to triage and resolve issues relating to CPU, memory, and GPU utilisation