Back
Metro location and senior engineering title increase competition, niche AI-reconciliation and automotive specificity limit applicant pool.
Core backend and data skills transfer, but automotive, reconciliation, and LLM guardrail experience create moderate domain bias.
Explicit 8+ years requirement plus mandatory Python/Django/Postgres/LLM and reconciliation expertise raises filter strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead the technical foundation and architecture for an AI-native automotive operating system at an early-stage startup.
Own critical system components including data reconciliation engine, AI grounding layer, integrations, multi-tenant security, and AI-native engineering standards.
Collaborate closely with founders, CTO, customers, and dealerships to build operationally grounded, scalable systems and help grow the engineering team and culture.
8+ years of professional experience building production systems.
Strong expertise in Python, Django, DRF, Celery, and PostgreSQL including advanced features like Row-Level Security and multi-tenant patterns.
Experience with data reconciliation across messy external systems and managing ORM migrations with evolving schemas.
Practical experience with LLMs, Retrieval-Augmented Generation (RAG), and AI coding agents, including implementing guardrails and maintaining AI output accuracy.
Technical leader comfortable with hands-on coding in early-stage, ambiguous environments building new platforms from scratch.
Systems thinker with experience in complex data integration, AI-native software engineering, and scalable event-driven architectures.
Able to collaborate directly with customers and stakeholders, challenge unrealistic timelines, and establish high-quality AI and engineering practices for a growing team.