Job description

Founding Forward Deployed Engineer We are partnering with a fast-growing AI startup in New York that is building an agentic platform designed to transform how enterprise businesses identify and execute revenue opportunities. This is a particularly interesting opportunity for someone who sits at the intersection of data engineering, software engineering, AI and customers. What you will be doing: You will own customer deployments from initial data access through to production, including: • Exploring complex, undocumented data warehouses and understanding how the underlying data actually works • Mapping messy schemas onto real business concepts including ARR, churn, expansion and revenue • Writing and validating complex SQL across customer data environments • Building the semantic and ontology layers that sit between raw enterprise data and AI agents • Working with customer stakeholders to uncover tribal knowledge and resolve conflicting definitions of key metrics • Deploying production AI agent workflows and data pipelines into customer environments • Testing and validating outputs to ensure AI systems are reliable before they influence real business decisions What we are looking for: We are looking for an engineer with approximately 2-5 years of experience who is comfortable being given a difficult customer problem and owning the technical solution. You should have: • Deep SQL and data warehouse experience • The ability to navigate messy, legacy or undocumented schemas independently • Experience with dbt and modern data engineering workflows • Strong Python skills • Experience building and shipping production data pipelines or software systems • Previous ownership of technical customer deployments, from initial discovery through implementation and proving value • Confidence working directly with technical and non-technical customer stakeholders • A strong quantitative academic background in Computer Science, Data Science, Statistics, Mathematics, Engineering or a related discipline Cavendish (Recruitment) Professionals Ltd is proud to be an equal opportunities employer, and we believe that inclusion starts with the applicant. All qualified candidates will be considered for employment regardless of gender, race, age, sexual orientation, religion or belief.

Requirements

Must-haves

Founding Forward Deployed Engineer
We are partnering with a fast-growing AI startup in New York that is building an agentic platform designed to transform how enterprise businesses identify and execute revenue opportunities.
This is a particularly interesting opportunity for someone who sits at the intersection of data engineering, software engineering, AI and customers.
You will own customer deployments from initial data access through to production, including:
Exploring complex, undocumented data warehouses and understanding how the underlying data actually works
Mapping messy schemas onto real business concepts including ARR, churn, expansion and revenue
Writing and validating complex SQL across customer data environments
Building the semantic and ontology layers that sit between raw enterprise data and AI agents
Working with customer stakeholders to uncover tribal knowledge and resolve conflicting definitions of key metrics
Deploying production AI agent workflows and data pipelines into customer environments
Testing and validating outputs to ensure AI systems are reliable before they influence real business decisions
We are looking for an engineer with approximately 2-5 years of experience who is comfortable being given a difficult customer problem and owning the technical solution.
Deep SQL and data warehouse experience
The ability to navigate messy, legacy or undocumented schemas independently
Experience with dbt and modern data engineering workflows
Strong Python skills
Experience building and shipping production data pipelines or software systems
Previous ownership of technical customer deployments, from initial discovery through implementation and proving value
Confidence working directly with technical and non-technical customer stakeholders
A strong quantitative academic background in Computer Science, Data Science, Statistics, Mathematics, Engineering or a related discipline

Nice-to-haves

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Keywords to mirror

aisqlpython

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