Lead Software Engineer

Overview

The Lead Software Engineer, AI & Platform is a hands-on technical leader responsible for advancing Churchstreeter & Crosse’s proprietary healthcare talent technology SaaS platform. Working closely with the CEO, this role architects and builds production software, develops advanced AI capabilities, delivers enterprise integrations, and coordinates technical execution across internal engineers, international teams, and external development partners. This is a builder-leader position requiring direct coding, strong architectural judgment, and accountability for secure, scalable, maintainable technology and the company’s intellectual property.

Key Responsibilities:

Platform Architecture & Development: Translate product vision into technical architecture, specifications, milestones, and executable engineering plans; personally design, write, debug, and improve production SaaS code.

AI Engineering: Lead the design and implementation of production AI capabilities, including RAG, embeddings, tool calling, structured outputs, agentic workflows, evaluation, guardrails, and human oversight.

Enterprise Integrations: Architect reliable integrations using APIs, webhooks, authentication, asynchronous processing, data synchronization, monitoring, and failure recovery.

Distributed Engineering Leadership: Coordinate U.S.-based and international engineers, contractors, and partners; assign workstreams, manage dependencies, set acceptance criteria, and establish effective cross-time-zone handoffs.

Technical Quality & Accountability: Review architecture and code from internal and external contributors; establish standards for testing, documentation, deployment, security, and maintainability; hold partners accountable for delivery.

Engineering Operations: Implement CI/CD, automated testing, observability, logging, monitoring, and effective technical documentation and knowledge transfer.

Security & Risk Management: Identify technical debt, scalability limits, integration risks, and security or privacy concerns early; incorporate reliability, governance, and protection of sensitive data throughout the platform.

Product & Executive Collaboration: Partner with product, business, and executive stakeholders to evaluate tradeoffs, communicate progress and blockers, and align technical delivery with the product roadmap.

Technical Ownership & Mentorship: Mentor engineers while remaining hands-on; ensure critical code, documentation, institutional knowledge, and intellectual property remain under Churchstreeter & Crosse’s control.

Qualifications

8+ years of progressive professional software engineering experience, including meaningful Senior, Lead, Staff, Principal, or comparable engineering responsibilities.

Demonstrated success architecting, building, launching, and scaling production SaaS applications, with current hands-on coding and debugging capability.

Experience leading technical execution across distributed, international, and contracted engineering teams while personally contributing production code.

Strong backend architecture, API, database, cloud infrastructure, and modern software design experience.

Production experience building AI-enabled applications, with working knowledge of LLMs, RAG, vector retrieval, agentic workflows, AI evaluation, observability, and model tradeoffs.

Experience implementing complex enterprise integrations and designing for resilience, security, monitoring, and recovery.

Experience establishing code review, architecture, testing, CI/CD, documentation, security, and operational quality standards.

Ability to turn product requirements into technical plans, assess risks and technical debt, and communicate effectively with business and executive stakeholders.

Preferred Experience

Enterprise B2B or multi-tenant SaaS; healthcare, HR, talent acquisition, workforce or people analytics technology; HCM/HRIS platforms; Workday, Phenom, Infor, Oracle, SAP SuccessFactors or similar integrations; high-volume integrations; sensitive employee, candidate, or healthcare data; data-intensive analytics; AI workflow automation; and assuming ownership of software built by external partners.

Education

Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, AI, Machine Learning, Data Science, or a related technical field preferred. Advanced degrees and relevant cloud, cybersecurity, or AI certifications are valued; demonstrated engineering ability remains essential.