Kumo
AI Engineer - Relational Foundation Models & Agentic Systems
Kumo, Mountain View, California, us, 94039
Why this role (and why now)
With the launch of our new
Kumo Relational Foundation Model (RFM) , we’ve seen
unprecedented interest from builders
who want to create on top of our platform. This is your chance to be part of that momentum. You’ll be
building applications and agentic workflows , demoing them to customers, and making
core product and engineering decisions
that shape the growth of our RFM offering. This is an engineering role at its core, but you’ll also
interface directly with customers, the broader builder community, and cross-functional engineering teams . We’re looking for someone who thrives in that hybrid space—shipping product, representing engineering externally, and helping shape the direction of Kumo RFM from the ground up. We’re looking for someone who’s:
Comfortable in an
innovation pod
or startup environment, moving quickly from idea → prototype → ship. A
tinkerer at heart
who’s built full‑stack apps (frontend, backend, data) and lately has been hands‑on with the
LLM tooling ecosystem . Collaborative and easy to work with —you know how to partner with PMs/design/ML, bounce ideas, and get things done together. Bonus: experience as a
Founding Engineer
or early builder who has shaped product direction from the ground up. About Kumo
Kumo.ai is redefining enterprise AI with
foundation models for relational data , enabling organizations to
predict, optimize, and act
with speed and confidence. Our agentic systems collaborate with data teams, turning complex business tables and SQL workflows into
interpretable, actionable, and automated
insights. The Role
We’re hiring an
AI/ML Engineer
to design and build
AI-powered, user-facing products
on top of our RFM. You’ll ship features that: Understand a user’s goal and
autonomously propose workflows
for analysis, prediction, and optimization. Interact with enterprise systems and APIs , orchestrating tools and data. Produce
interpretable outputs
that are easy to trust in real-world decisions. Demo prototypes and apps to customers , iterating on feedback and incorporating real use cases. You’ll work across product surfaces (UI/API), agent orchestration, data/infra, and model integration, collaborating tightly with product, design, ML research, and customers. What You\'ll Do Design, implement, and deploy
AI agents
that assist data scientists on
relational/SQL data
and recommend
next-best actions . Build
user-centric APIs and product surfaces
(web/UI or programmatic) that make agentic workflows feel seamless and reliable. Integrate Kumo’s
Relational Foundation Model
with enterprise data systems; contribute to
tooling, retrieval, and guardrails . Develop
adaptive, multi-step workflows
(LLM orchestration, tool use, feedback loops) that continuously refine outputs. Ensure
interpretability
and
evaluation : traceability of steps, confidence scoring, and human-in-the-loop review. Collaborate with PM/design/ML research to turn ambiguous problems into
shippable product ; instrument, measure, iterate. Demo your work to customers and community , serving as a visible builder and advocate for Kumo RFM. Optimize for
latency, cost, and reliability
in production environments (serving, caching, tracing, observability). Minimum Qualifications
1+ years
in ML/AI product development or software engineering (startup or fast-paced product teams). Hands-on with
embeddings, vector databases, and RAG ; practical experience evaluating retrieval quality. Strong background in
deep learning/transformers/foundation models
and
LLM orchestration
(tool use, planning, memory). Experience with
relational data & SQL ; structured reasoning on business datasets. Proficiency in
Python
and familiarity with
data wrangling
(Pandas, NumPy). Strong
product sense
and collaboration skills—comfortable working with PMs/design and iterating with users. Preferred Qualifications
Experience as a
Founding Engineer
or early builder at a startup/innovation pod. Experience with
LangChain, LangGraph, LlamaIndex ,
OpenAI/Anthropic
APIs, and
multi-agent coordination
libraries. Track record building
full-stack
features (you can dip into
frontend/backend/data/infra
as needed). Experience integrating agents with
enterprise systems and APIs ; designing
foundation APIs
for tools. Background in
knowledge graphs, GNNs, causal inference , or structured reasoning with LLMs. MLOps and cloud (AWS/GCP),
model/agent serving , prompt/runtime observability, and
eval pipelines . Familiarity with
guardrails, safety, and governance
for enterprise AI. How You\'ll Work Here
Builder mindset:
you ship small, learn fast, and raise the bar with each iteration. Team-first:
crisp communication, lightweight docs, and pairing with PM/design/ML to de-risk quickly. User-obsessed:
you instrument everything, close the loop with customers, and let usage guide the roadmap. Pragmatic about research:
you know when to use existing models vs. when to push the frontier. Success Looks Like (first 3-6 months)
Ship a
v1 agentic workflow
powered by RFM that users adopt for a real analytics task (with instrumented evals & feedback). Demonstrate
measurable improvements
(accuracy/latency/cost/UX trust) via experiments and A/Bs. Land 1–2
integrations
with enterprise data systems or tooling; document
runbooks
and
guardrails . Deliver
customer demos
that inspire adoption and open new product opportunities. Our Stack
Python ,
Pandas/NumPy ,
PyTorch/JAX/TensorFlow ,
LangChain/LangGraph/LlamaIndex ,
OpenAI/Anthropic APIs , vector DBs, SQL, modern web stack (we’ll meet you where you are), AWS/GCP, observability/tooling for agents. Salary:
$125,000 - $175,000 a year Why join Kumo
• Shape the future of
AI for structured data
with a truly differentiated
Relational Foundation Model . • Build
net-new agent experiences
that make data teams faster and more effective. • Work with a small, senior team that ships—
high impact, low bureaucracy
. • Be an early voice in growing Kumo’s RFM product—
influence direction, ship demos, and help define the category
. Kumo.ai is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
#J-18808-Ljbffr
With the launch of our new
Kumo Relational Foundation Model (RFM) , we’ve seen
unprecedented interest from builders
who want to create on top of our platform. This is your chance to be part of that momentum. You’ll be
building applications and agentic workflows , demoing them to customers, and making
core product and engineering decisions
that shape the growth of our RFM offering. This is an engineering role at its core, but you’ll also
interface directly with customers, the broader builder community, and cross-functional engineering teams . We’re looking for someone who thrives in that hybrid space—shipping product, representing engineering externally, and helping shape the direction of Kumo RFM from the ground up. We’re looking for someone who’s:
Comfortable in an
innovation pod
or startup environment, moving quickly from idea → prototype → ship. A
tinkerer at heart
who’s built full‑stack apps (frontend, backend, data) and lately has been hands‑on with the
LLM tooling ecosystem . Collaborative and easy to work with —you know how to partner with PMs/design/ML, bounce ideas, and get things done together. Bonus: experience as a
Founding Engineer
or early builder who has shaped product direction from the ground up. About Kumo
Kumo.ai is redefining enterprise AI with
foundation models for relational data , enabling organizations to
predict, optimize, and act
with speed and confidence. Our agentic systems collaborate with data teams, turning complex business tables and SQL workflows into
interpretable, actionable, and automated
insights. The Role
We’re hiring an
AI/ML Engineer
to design and build
AI-powered, user-facing products
on top of our RFM. You’ll ship features that: Understand a user’s goal and
autonomously propose workflows
for analysis, prediction, and optimization. Interact with enterprise systems and APIs , orchestrating tools and data. Produce
interpretable outputs
that are easy to trust in real-world decisions. Demo prototypes and apps to customers , iterating on feedback and incorporating real use cases. You’ll work across product surfaces (UI/API), agent orchestration, data/infra, and model integration, collaborating tightly with product, design, ML research, and customers. What You\'ll Do Design, implement, and deploy
AI agents
that assist data scientists on
relational/SQL data
and recommend
next-best actions . Build
user-centric APIs and product surfaces
(web/UI or programmatic) that make agentic workflows feel seamless and reliable. Integrate Kumo’s
Relational Foundation Model
with enterprise data systems; contribute to
tooling, retrieval, and guardrails . Develop
adaptive, multi-step workflows
(LLM orchestration, tool use, feedback loops) that continuously refine outputs. Ensure
interpretability
and
evaluation : traceability of steps, confidence scoring, and human-in-the-loop review. Collaborate with PM/design/ML research to turn ambiguous problems into
shippable product ; instrument, measure, iterate. Demo your work to customers and community , serving as a visible builder and advocate for Kumo RFM. Optimize for
latency, cost, and reliability
in production environments (serving, caching, tracing, observability). Minimum Qualifications
1+ years
in ML/AI product development or software engineering (startup or fast-paced product teams). Hands-on with
embeddings, vector databases, and RAG ; practical experience evaluating retrieval quality. Strong background in
deep learning/transformers/foundation models
and
LLM orchestration
(tool use, planning, memory). Experience with
relational data & SQL ; structured reasoning on business datasets. Proficiency in
Python
and familiarity with
data wrangling
(Pandas, NumPy). Strong
product sense
and collaboration skills—comfortable working with PMs/design and iterating with users. Preferred Qualifications
Experience as a
Founding Engineer
or early builder at a startup/innovation pod. Experience with
LangChain, LangGraph, LlamaIndex ,
OpenAI/Anthropic
APIs, and
multi-agent coordination
libraries. Track record building
full-stack
features (you can dip into
frontend/backend/data/infra
as needed). Experience integrating agents with
enterprise systems and APIs ; designing
foundation APIs
for tools. Background in
knowledge graphs, GNNs, causal inference , or structured reasoning with LLMs. MLOps and cloud (AWS/GCP),
model/agent serving , prompt/runtime observability, and
eval pipelines . Familiarity with
guardrails, safety, and governance
for enterprise AI. How You\'ll Work Here
Builder mindset:
you ship small, learn fast, and raise the bar with each iteration. Team-first:
crisp communication, lightweight docs, and pairing with PM/design/ML to de-risk quickly. User-obsessed:
you instrument everything, close the loop with customers, and let usage guide the roadmap. Pragmatic about research:
you know when to use existing models vs. when to push the frontier. Success Looks Like (first 3-6 months)
Ship a
v1 agentic workflow
powered by RFM that users adopt for a real analytics task (with instrumented evals & feedback). Demonstrate
measurable improvements
(accuracy/latency/cost/UX trust) via experiments and A/Bs. Land 1–2
integrations
with enterprise data systems or tooling; document
runbooks
and
guardrails . Deliver
customer demos
that inspire adoption and open new product opportunities. Our Stack
Python ,
Pandas/NumPy ,
PyTorch/JAX/TensorFlow ,
LangChain/LangGraph/LlamaIndex ,
OpenAI/Anthropic APIs , vector DBs, SQL, modern web stack (we’ll meet you where you are), AWS/GCP, observability/tooling for agents. Salary:
$125,000 - $175,000 a year Why join Kumo
• Shape the future of
AI for structured data
with a truly differentiated
Relational Foundation Model . • Build
net-new agent experiences
that make data teams faster and more effective. • Work with a small, senior team that ships—
high impact, low bureaucracy
. • Be an early voice in growing Kumo’s RFM product—
influence direction, ship demos, and help define the category
. Kumo.ai is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
#J-18808-Ljbffr