About this role
We are building a team of engineers in Edmonton, AB, Canada to develop a first-of-its-kind synthetic persona platform — an AI system that models human behavior, preferences, and decision-making at scale. This role sits at the intersection of software engineering, data engineering and applied AI: you will design the pipelines that power the personas and , the models and the platform deployments that bring them to life.
This is not a maintenance role. The platform is being built from the ground up, and every technical decision you make will shape what it becomes. You will work alongside researchers, data scientists, and product engineers in a small, high-trust team where curiosity and ownership are the norm.
What You Will Do
Design and build a scalable platform and the data pipelines that ingest, transform, and serve structured and unstructured data to AI modelsDevelop and iterate on AI/ML components — including LLM-based agents, embedding models, and behavioral simulation layers — that power synthetic persona generationArchitect and maintain the data infrastructure underpinning persona modeling: feature stores, vector databases, data lakes, and real-time serving layersCollaborate with researchers to translate persona logic and behavioral frameworks into working system componentsWrite production-quality code, participate in code reviews, and contribute to engineering standards for the teamMonitor model and pipeline performance in production; identify and resolve issues proactivelyContribute to system design discussions and help shape the technical roadmap Must be able to commute to our Edmonton, AB, Canada office
Core Technical Skills
3–5 years of hands-on experience in software engineering, data engineering, ML engineering, or a closely related roleProficiency in Python and at least one data processing framework (Spark, dbt, Airflow, Prefect, or similar)Experience building and deploying ML models or AI components in a production environmentFamiliarity with LLMs and modern AI tooling: prompt engineering, fine-tuning, RAG pipelines, orand agent frameworks (LangChain, LangGraph LlamaIndex, CrewAI, or equivalent)Solid understanding of data modeling, schema design, and the tradeoffs between different storage paradigms (relational, document, vector, columnar)Experience with cloud data infrastructure — AWS, GCP, or Azure — and comfort operating in a cloud-native environmentSystems & Engineering Mindset
Ability to reason about system architecture: latency, throughput, scalability, and data consistency tradeoffsExperience with APIs, microservices, or event-driven architectures (Kafka, Pub/Sub, or similar)Comfort working across the stack — from raw data ingestion through to model serving and API exposureStrong debugging instincts and a habit of writing observable, testable codeHow You Work
Intrinsically motivated — you pursue hard problems because they interest you, not because someone handed you a ticketComfortable with ambiguity; you can move forward when the requirements are still formingCollaborative by default — you ask questions, share context early, and bring others alongYou read papers, experiment on weekends, and have opinions about how AI systems should be builtNice to Have
Experience with SnowflakeExperience with behavioral modeling, simulation, or agent-based systemsBackground in NLP, computational social science, or user modelingContributions to open-source AI or data toolingFamiliarity with synthetic data generation techniques or privacy-preserving MLExperience working in a startup or early-stage product environment Synthetic personas are one of the most technically interesting and practically consequential challenges in applied AI right now. The platform you help build will be used to simulate human decision-making in ways that have real product and business impact. You will have direct influence over architectural decisions, meaningful ownership of your components, and a front-row seat to a research area that is evolving fast.
*Must be able to work on-site at our Edmonton, AB, Canada location