Founding Engineer – (Backend, Front End, Data, Full Stack)
Alldus International Consulting Ltd, San Francisco, CA, United States
Our client, an early-stage AI Startup, is hiring a Founding Engineer to join their team in San Francisco. The successful candidate will play a key role in designing and scaling a multi‑tenant, AI‑native platform, from building the semantic foundation that allows autonomous agents to interpret data and take action across sources ranging from ERP systems to unstructured documents and real‑world signals.
Responsibilities
Design and develop scalable data ingestion and transformation pipelines across both structured and unstructured data sources.
Build and maintain a robust connector framework for integrating enterprise systems (ERP, CRM, PLM, legacy databases, emails, documents and spreadsheets).
Architect and evolve the Data Fabric layer, including knowledge graphs and semantic data models.
Prepare and vectorize data to support AI use cases such as RAG, summarization and intelligent alerting.
Establish and manage data governance, lineage, and access control frameworks.
Develop secure, well‑designed APIs to enable access to enriched data across services and autonomous agents.
Partner closely with ML teams to support model training, optimization and deployment pipelines.
Skillset
At least five years' experience building production‑grade data infrastructure.
Strong expertise in ETL/ELT pipelines, including tools such as Kafka, Airbyte, Fivetran and Meltano.
Proven experience with workflow orchestration platforms such as Airflow, Dagster or Prefect.
Hands‑on experience processing unstructured data, including PDFs, emails, logs, spreadsheets and APIs.
Familiarity with lakehouse architectures and formats such as Iceberg, Delta and Parquet.
Solid understanding of graph databases and semantic modelling, including technologies like Neo4j, RDF and Gremlin.
Strong API design capabilities, with experience in GraphQL and RESTful services.
Experience implementing data governance frameworks, including RBAC, ABAC, data lineage, and quality controls.
Benefits
Salary: $140k - $180k
Equity
#J-18808-Ljbffr
Responsibilities
Design and develop scalable data ingestion and transformation pipelines across both structured and unstructured data sources.
Build and maintain a robust connector framework for integrating enterprise systems (ERP, CRM, PLM, legacy databases, emails, documents and spreadsheets).
Architect and evolve the Data Fabric layer, including knowledge graphs and semantic data models.
Prepare and vectorize data to support AI use cases such as RAG, summarization and intelligent alerting.
Establish and manage data governance, lineage, and access control frameworks.
Develop secure, well‑designed APIs to enable access to enriched data across services and autonomous agents.
Partner closely with ML teams to support model training, optimization and deployment pipelines.
Skillset
At least five years' experience building production‑grade data infrastructure.
Strong expertise in ETL/ELT pipelines, including tools such as Kafka, Airbyte, Fivetran and Meltano.
Proven experience with workflow orchestration platforms such as Airflow, Dagster or Prefect.
Hands‑on experience processing unstructured data, including PDFs, emails, logs, spreadsheets and APIs.
Familiarity with lakehouse architectures and formats such as Iceberg, Delta and Parquet.
Solid understanding of graph databases and semantic modelling, including technologies like Neo4j, RDF and Gremlin.
Strong API design capabilities, with experience in GraphQL and RESTful services.
Experience implementing data governance frameworks, including RBAC, ABAC, data lineage, and quality controls.
Benefits
Salary: $140k - $180k
Equity
#J-18808-Ljbffr