Our team builds Celonis' end-to-end Task Mining solution.
Key Responsibilities
We're looking for a Senior Software Engineer to help shape the AI and algorithmic core of Task Mining. Our mission is broad and growing: turning raw signals about how people work into structured, actionable insight.
You'll design the algorithms and AI techniques behind these capabilities and ship them as robust, production-grade services to our customers. This is a role for someone who is energized by AI and algorithms first, and equally comfortable building the scalable services and data pipelines that deliver those capabilities reliably at enterprise scale. You'll work primarily in Python, with SQL across our data pipeline, and touch Java on the wider backend where it matters. You'll set technical direction, raise the engineering bar, and mentor others along the way.
Design and build AI- and algorithm-powered features from scratch — from research and prototyping through to production rollout — across a growing set of problems.
Advance our core insight engine: evolve techniques that combine LLMs, machine learning, and rule-based/algorithmic methods to extract structure from complex, noisy interaction data — keeping results accurate, explainable, and cost-efficient.
Integrate new and diverse data sources into the product, designing the abstractions that let us plug them in cleanly.
Develop and deploy production-ready Python services — clean async APIs, containerized and integrated into a multi-tenant SaaS platform — to serve our AI and data pipelines.
Build and extend robust, scalable data pipelines for ingesting, processing, and transforming large datasets, and design the data models behind them.
Build strong evaluation into everything: guardrails, hallucination and schema-adherence checks, and latency/cost/quality metrics, so we can trust and continuously improve model and algorithm outputs.
Own end-to-end delivery: lead design, implementation, build, and shipping to customers.
Provide technical leadership and mentorship — drive design discussions, code reviews, and technical planning to keep standards high and knowledge shared.
Requirements
5+ years of practical experience in a Computer Science / Data Science related field, or a PhD in Data Science/AI/ML with 2+ years of practical experience.
Hands-on experience applying AI/ML to real problems — including LLMs and Retrieval-Augmented Generation (RAG): writing effective prompts, using vector search, and evaluating outputs for hallucination, schema adherence, and performance (latency/cost).
A strong algorithmic foundation and the judgment to choose between AI-based and classical approaches for a given problem.
Experience designing, building, and deploying robust, scalable, production-ready Python services and APIs.
Strong understanding of Python's async I/O model and why it matters for high-performance, I/O-bound applications.
Solid grasp of ETL, data warehouses/lakes, data modeling, and schema design.
Experience with containerization (Docker) and CI/CD (e.g. GitHub Actions).
Strong communication and collaboration skills (English is a must).
Ready to Apply?
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