Job VC
Staff Engineer, Production Intelligence (Knowledge Graph / AI Systems)
Technologies
Description
About the Role
We are looking for a highly experienced
Staff Engineer
to build and own a next-generation production intelligence platform at the intersection of
AI, infrastructure, and data systems
.
This role goes beyond traditional backend or data engineering — it focuses on designing a
knowledge graph layer
that enables AI systems to understand and reason about complex production environments in real time.
You will be one of the first engineers in this domain area, with full ownership of architecture and key technical decisions.
What You Will Do
Design and own a
production knowledge graph architecture
(schema, entities, relationships, temporal modeling)
Build
data ingestion pipelines
from multiple sources (CI/CD, infrastructure, cloud systems, streaming platforms)
Define strategies for handling
high-volume, high-cardinality production data
Develop a
semantic layer
enabling intelligent querying and reasoning over the system
Ensure
data consistency, quality, and long-term coherence
Work closely with engineering leadership on architecture and system design
Validate solutions against real-world production environments
Requirements
10+ years of experience in backend or systems engineering
Strong hands-on experience with
graph databases (Neo4j preferred)
Proven experience building
scalable data ingestion pipelines
Deep understanding of
distributed systems and cloud-native infrastructure
Experience with
Kubernetes, CI/CD, and modern DevOps practices
Strong data modeling skills (entities, relationships, versioning, schema design)
Ability to make architectural decisions independently in a fast-paced environment
Nice to Have
Experience with
infrastructure graph tools
(e.g., Cartography or similar)
Experience working with
AI/ML systems or LLM-based architectures
Familiarity with
event-driven systems (Kafka, streaming)
Background in
knowledge graphs or semantic systems
Tech Stack
Neo4j, Python, Kafka, Kubernetes, PostgreSQL, Graph-based tooling, cloud infrastructure
What Makes This Role Unique
This is not a typical backend or data role. You will be building the
core knowledge layer
that enables AI systems to reason about production environments.
You will:
Own the architecture from day one
Make high-impact technical decisions
Work on a product that sits at the intersection of
AI + infrastructure + data
Hiring Process
2–3 interview stages
Technical + system design focus
We are looking for a highly experienced
Staff Engineer
to build and own a next-generation production intelligence platform at the intersection of
AI, infrastructure, and data systems
.
This role goes beyond traditional backend or data engineering — it focuses on designing a
knowledge graph layer
that enables AI systems to understand and reason about complex production environments in real time.
You will be one of the first engineers in this domain area, with full ownership of architecture and key technical decisions.
What You Will Do
Design and own a
production knowledge graph architecture
(schema, entities, relationships, temporal modeling)
Build
data ingestion pipelines
from multiple sources (CI/CD, infrastructure, cloud systems, streaming platforms)
Define strategies for handling
high-volume, high-cardinality production data
Develop a
semantic layer
enabling intelligent querying and reasoning over the system
Ensure
data consistency, quality, and long-term coherence
Work closely with engineering leadership on architecture and system design
Validate solutions against real-world production environments
Requirements
10+ years of experience in backend or systems engineering
Strong hands-on experience with
graph databases (Neo4j preferred)
Proven experience building
scalable data ingestion pipelines
Deep understanding of
distributed systems and cloud-native infrastructure
Experience with
Kubernetes, CI/CD, and modern DevOps practices
Strong data modeling skills (entities, relationships, versioning, schema design)
Ability to make architectural decisions independently in a fast-paced environment
Nice to Have
Experience with
infrastructure graph tools
(e.g., Cartography or similar)
Experience working with
AI/ML systems or LLM-based architectures
Familiarity with
event-driven systems (Kafka, streaming)
Background in
knowledge graphs or semantic systems
Tech Stack
Neo4j, Python, Kafka, Kubernetes, PostgreSQL, Graph-based tooling, cloud infrastructure
What Makes This Role Unique
This is not a typical backend or data role. You will be building the
core knowledge layer
that enables AI systems to reason about production environments.
You will:
Own the architecture from day one
Make high-impact technical decisions
Work on a product that sits at the intersection of
AI + infrastructure + data
Hiring Process
2–3 interview stages
Technical + system design focus