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About the team
Money generates incredibly rich behavioural data.
At slice, we're building the intelligence layer that transforms raw financial signals into context-aware, personalised user experiences. This team sits at the intersection of backend engineering, distributed systems, and applied AI.
We are building an AI-first banking experience. Not AI features sprinkled on top, but core intelligence that understands patterns, correlations, and intent across user behaviour. This is where backend architecture meets agentic AI systems.
About the role
We are looking for a Staff Engineer to join our AI Pod. This is a high-impact, hands-on individual contributor role. You will define and architect the backend foundations that power AI-native experiences across the slice ecosystem.
You will operate at the intersection of distributed systems, large-scale data, and production-grade AI systems. This role requires both strong backend fundamentals and deep practical experience deploying AI/LLM-powered systems in production.
What You will do
What You will need
Bonus points if you've:
What makes this role unique
You will be part of the founding layer of slice's AI Pod, shaping how intelligence is embedded into a banking experience from first principles.
Life at slice
Life so good, you'd think we're kidding:
Job ID: 147369515
Skills:
Distributed Systems, Python, agentic system architectures, benchmarking pipelines, automation evaluation frameworks, CI CD pipelines, debugging skills
Skills:
Java, Machine Learning, Jax, Deep Learning, Tensorflow, Pytorch, Python, diffusion, Transformers, LLMs, generative AI, Go, ML frameworks
Skills:
snowflake , Machine Learning, Kafka, Sql, Data Science, MLops, Spark, Databricks, Python, Probabilistic modeling, Airflow, Generative AI, LLMs, Feature engineering, Transformers, Tree-based models
Skills:
Java, Graphql, Scala, Kafka, TigerGraph, MLops, Neo4j, Docker, Spark, Kubernetes, Python, AWS, Airflow, pgvector, Qdrant, Go, MLflow, Flink, Neptune, Kubeflow, Milvus
Skills:
Java, Machine Learning, Hadoop, Scala, Kafka, Sql, Nosql, Tensorflow, Pytorch, Gcp, Docker, Spark, Azure, Kubernetes, Python, AWS, scikit-learn
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