Senior Software Engineer – AI, Data

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Create the data and reasoning frameworks for Codat's Advisory Intelligence Platform.

• Build the semantic layer of measures, dimensions, and definitions utilized by the AI assistant.

• Design and construct the signal layer that identifies changes for clients.

• Develop the reasoning layer, inclusive of calculations and structures employed by Codat's LLM.

• Create agents and MCP servers, which encompass tools, failure management, and evaluations.

• Develop pipelines, services, and data models that transition raw source data into assistant responses.

• Implement testing and observability measures to ensure data accuracy.

• Generate evaluations to identify when the model references incorrect data.

• Take ownership of systems from development to production operations.

• Collaborate with engineering, product, and commercial teams to shape product direction.

⛳️ Requirements

• Experience building production systems from the ground up, focusing on coding rather than configuring managed services.

• Proven experience in designing interfaces, handling failure modes, and producing maintainable code.

• Background in serving data to an LLM and familiarity with challenges such as ambiguous definitions, ineffective retrieval, and insufficient evaluations.

• Experience with data pipelines, data shaping, and systems for serving data.

• Proficiency in C#, Python, or another backend programming language.

• Expertise in at least one of the following: SQL, Spark, Databricks/Delta Lake, Dagster/Airflow/Temporal, or dbt.

• Knowledge of CI/CD practices, Docker, cloud infrastructure, and observability tools.

• Familiarity with Azure cloud services.

• Interest in the business context of data and the capability to establish guardrails.

• Experience designing personal workflows with AI automation.

🏝️ Benefits

• Equity.

• No requirement to return to the office.

• Options for hybrid or fully remote work.

• Flexible work arrangements.

• Trust and autonomy in how and where work is conducted.