About this role
Cognisity is an early-stage GovTech AI company seeking a Founding Head of Engineering & Technical Operations to serve as the company's technical leader and operational backbone. This is a foundational leadership role for an experienced engineering executive who can bridge strategy and execution—driving technical architecture, engineering excellence, operational rigor, and scalable product delivery. Working closely with the Founder/CEO and cross-functional teams spanning Product, AI/Data Science, Solutions, QA, and outsourced engineering, this leader will transform complex property assessment workflows into reliable, production-grade software while establishing the technical processes needed to support rapid growth. Cognisity is building an AI-powered intelligence platform for county assessor offices, helping governments improve property assessment accuracy, identify missed revenue opportunities, and support defensible valuation decisions through data, geospatial intelligence, and AI-driven analysis. The company's long-term vision is to become the AI operating platform for property assessment and revenue integrity across the United States. Beyond leading engineering execution, this role will reduce founder dependency, strengthen cross-functional alignment, and ensure technology investments directly support business objectives. As the company scales, this individual is expected to become the CEO's long-term technical partner with the opportunity to evolve into the Chief Technology Officer (CTO) role. KEY RESPONSIBILITIES Engineering Leadership and Technical Ownership Own Cognisity’s engineering roadmap and technical execution plan. Translate company, customer, and product priorities into an achievable engineering plan. Make architecture and sequencing decisions that balance speed, reliability, scalability, cost, and customer readiness. Create clarity around what should be built now, what should be hardened, what should be deferred, and what should become reusable platform infrastructure. Help the company avoid technical debt that would slow future county deployments. Build toward a scalable technical foundation rather than one-off demos or custom implementations. Technical Operations and Business Execution Help the CEO manage the technical side of the business. Bring operating discipline to engineering planning, delivery, release readiness, and cross-functional execution. Help prioritize technical work against customer commitments, business milestones, funding goals, and resource constraints. Understand how engineering choices affect product margins, implementation costs, customer delivery, and scalability. Support weekly operating cadence, milestone tracking, vendor accountability, and technical risk management. Help determine when to move fast with prototypes versus when to invest in production-grade infrastructure. Act as a practical thought partner to the CEO on technical hiring, vendor strategy, product sequencing, and business tradeoffs. Manage and Upgrade Outsourced Engineering Execution Act as the internal technical owner for the outsourced engineering team. Improve sprint planning, technical scoping, code review, release discipline, and accountability. Ensure outsourced engineers are building toward Cognisity’s long-term platform architecture rather than only completing tickets. Identify what should remain outsourced versus what should be brought in-house. Help define and recruit the next internal engineering hires. Ensure vendor work is properly documented, maintainable, and aligned with Cognisity’s technical standards. Data Platform and Pipeline Reliability Own the architecture and reliability of data ingestion, transformation, storage, and processing pipelines. Work with data science and data engineering to improve repeatability, observability, and QA. Help productize workflows involving assessor roll data, permits, sales/comps, MLS, GIS/imagery, valuation logic, and assessment outputs. Ensure pipelines are scalable across counties and adaptable to different county data formats. Partner with QA to create data validation checks, anomaly detection, and repeatable test coverage. Reduce manual effort and rework as Cognisity expands to more modules and counties. Productization of AI/Data Science Work Work closely with AI/Data Science to turn research outputs, valuation logic, prompts, models, and scoring systems into reliable product features. Help define the handoff process from R&D to production. Ensure AI-assisted outputs are explainable, auditable, testable, and appropriate for human review. Support development of confidence scoring, evidence packages, comp selection workflows, Prop 8 logic, and escape assessment workflows. Build systems that support both automation and assessor review. Ensure that model outputs are integrated into usable workflows rather than remaining isolated analytical artifacts. Platform Architecture Own core platform architecture across backend, data, APIs, application layer, integrations, and cloud infrastructure. Make practical decisions around build-vs-buy, cloud architecture, data stores, orchestration, APIs, and internal tooling. Ensure the architecture can support multiple counties, modules, workflows, data refresh cycles, and customer environments. Prepare the platform for future integrations with CAMA, GIS, document management, and county systems. Build toward a scalable “intelligence layer” rather than a services-heavy implementation model. Customer / Pilot Technical Readiness Support technical planning for county demos, pilots, and design partner engagements. Help distinguish between demo-ready, pilot-ready, and production-ready functionality. Partner with Product Solutions to translate county-specific needs into reusable product capabilities. Ensure technical commitments made to customers are realistic and deliverable. Help prepare technical materials, architecture explanations, and implementation plans for county stakeholders when needed. Support Riverside / Prop 8 readiness and future county deployments. QA, Release, and Production Discipline Create a stronger engineering QA and release process. Partner with Product, Product Solutions, Data Science, and Data QA to define acceptance criteria. Improve testing practices across data pipelines, backend logic, UI features, and AI/data outputs. Create release checkpoints for demos, pilots, and production deployments. Ensure county-facing outputs are reliable, explainable, and defensible. Build a culture where quality, auditability, and trust are treated as core product requirements. Security, Privacy, and GovTech Readiness Help Cognisity prepare for county security, privacy, procurement, and integration expectations. Establish practical early-stage security practices without overbuilding. Support future SOC 2 / CJIS / government security readiness discussions as appropriate. Work with the founder and product team on technical responses for county evaluations, pilots, and procurement processes. Ensure the platform is designed with public-sector trust, data handling, and operational resilience in mind. Engineering Hiring and Team Building Help define the next internal engineering hires. Build a culture of ownership, quality, speed, product accountability, and customer awareness. Over time, help transition Cognisity from outsourced-heavy engineering to a more balanced internal team. Develop the foundation for a high-performing engineering organization. REQUIRED QUALIFICATIONS 8–15+ years of software engineering experience. Prior engineering leadership experience in a startup, growth company, enterprise SaaS company, GovTech company, PropTech company, data platform company, or AI/data-heavy product environment. Strong technical judgment across backend systems, data pipelines, APIs, cloud architecture, and application development. Experience managing internal and/or outsourced engineering teams. Experience building production systems, not just prototypes. Strong understanding of software development lifecycle, release discipline, testing, observability, and technical debt management. Ability to work closely with product, data science, design, QA, and customer-facing teams. Business judgment and ability to connect technical decisions to customer delivery, product scalability, implementation cost, and company priorities. Ability to recruit, assess, and manage engineers. Comfort working directly with a founder in a fast-moving, ambiguous environment. Strong written and verbal communication skills. Hands-on enough to review architecture, inspect implementation decisions, and unblock engineers. PREFERRED QUALIFICATIONS Experience with data-heavy SaaS platforms. Experience with AI/ML productization, model outputs, scoring systems, decision-support tools, or human-in-the-loop workflows. Experience with government, public sector, regulated industries, enterprise procurement, or security-conscious customers. Experience with geospatial, property, real estate, tax, insurance, lending, permitting, construction, or public-records data. Experience building platforms that ingest messy third-party data from multiple sources. Experience scaling from outsourced development to internal engineering. Experience with AWS or similar cloud platforms. Experience with Python, SQL, modern backend frameworks, data orchestration tools, API architecture, and modern front-end application development. Familiarity with data warehouse / relational database architecture. Experience implementing QA and release processes in an early-stage environment. Experience supporting enterprise or government customer implementations. Experience participating in business planning, fundraising diligence, board/investor discussions, or technical roadmap planning. WORK LOCATION Los Angeles / Southern California preferred. Hybrid, but this person must be highly available, collaborative, and able to work closely with the founder, product, data science, and engineering teams. Because Cognisity works with county and government customers, occasional travel for customer meetings, demos, planning sessions, and team meetings may be required. SALARY RANGE Base Salary: $200,000–$240,000 annually Equity: 1.5%–2.5%