Description review
Founding Engineering Lead
Clera · Remote - New York · back to the listing
HR standards
71/100
solid
Title ↔ description
79/100
solid
Reads as
Engineering Manager
90% confident
What this role officially is
software manager — ESCO, the EU occupation classification
Software managers oversee the acquisition and development of software systems in order to provide support to all organisational units. They also monitor the results and quality of the different software solutions and projects implemented in the organisation.
Also known as: applications manager, software managers, ICT applications manager, software applications manager, soft manager
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What the listing never says
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
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.
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.