Founding Engineering Lead

Clera

New York, NY

Remote

Who this role is best for

Experienced engineers with applied machine learning expertise and leadership experience will find this hands-on, on-site role in B2B SaaS with a small team and significant technical ownership responsibilities.

Best fit for

Experienced engineers with applied machine learning expertise and leadership experience will find this hands-on, on-site role in B2B SaaS with a small team and significant technical ownership responsibilities.
— “Join an early-stage B2B SaaS team as its hands-on engineering lead”
Candidates who have led small engineering teams and set technical standards will thrive in this role.
— “Experience setting engineering practices and holding a team accountable as a technical or people lead”
Individuals with a track record of shipping software end-to-end and making infrastructure decisions will align well with this role's demands.
— “Recent experience personally shipping software end-to-end”

Things to consider

On-site presence in New York City is mandatory, with no remote flexibility implied.
— “On-site in New York City”
The role requires a balance between hands-on coding and leadership responsibilities.
— “Lead a pod of three to four engineers, supporting their growth, performance, and hiring while remaining hands-on with key projects”

How to stand out

Emphasize end-to-end ownership of technical architecture and infrastructure decisions in your resume and interview.
— “End-to-end ownership of technical architecture, including infrastructure and build-versus-buy decisions”
Highlight your experience in deploying machine learning models, not just integrating third-party APIs.
— “Experience training and deploying machine learning models in production”
Demonstrate your ability to set and enforce engineering standards in your past roles.
— “Set engineering standards, code review criteria, release practices, definitions of done, and on-call policies”

Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

successful product launches
positive customer feedback

Typical background

software engineeringdata science

Skills & requirements

Required

Machine LearningSoftware ArchitectureCloud Infrastructure

Preferred

LeadershipProduct Management

Stack & domain

Machine LearningSoftware ArchitectureInfrastructure DecisionsCode ReviewRelease PracticesOn-call PoliciesTechnical DesignImplementationApplied Machine LearningProduct DirectionModel StrategyEngineering RoadmapLeadershipCommunicationProblem-solvingTeam ManagementTechnical GuidanceSoftware DevelopmentData ScienceEngineering

About the role

Original posting from Clera via Ashby

ABOUT THE ROLE
Join an early-stage B2B SaaS team as its hands-on engineering lead, shaping platform architecture and applied machine learning strategy alongside the technical founders. You will lead a small engineering pod while building and shipping critical product work, helping establish the technical foundation and practices for the team.
WHAT YOU'LL DO
Lead a pod of three to four engineers, supporting their growth, performance, and hiring while remaining hands-on with key projects.
Own core platform architecture, infrastructure decisions, build-versus-buy choices, and cost considerations.
Set engineering standards, code review criteria, release practices, definitions of done, and on-call policies.
Lead technical design and initial implementation for new initiatives.
Evaluate applied machine learning approaches and distinguish techniques ready for production from those that are still speculative.
Partner with the technical leadership team on product direction, model strategy, and the engineering roadmap.
WHAT WE'RE LOOKING FOR
Typically 5 to 8 years of engineering experience, with exceptional candidates who have 4 to 5 years also considered.
Experience training and deploying machine learning models in production, beyond integrating third-party LLM APIs.
End-to-end ownership of technical architecture, including infrastructure and build-versus-buy decisions.
Experience setting engineering practices and holding a team accountable as a technical or people lead.
Recent experience personally shipping software end-to-end, along with strong hands-on coding skills.
Applied ML judgment across classical methods and newer approaches, plus experience using AI coding agents effectively.
Comfort working through ambiguity, existing code, and practical delivery challenges.
COMPENSATION & BENEFITS
Base salary is $200,000 to $400,000 annually, with equity. Visa sponsorship is not available.
LOCATION
On-site in New York City.

Source: Clera careers (Ashby)