Founding Lead Engineer / Principal Systems Architect in United States at Jobgether
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Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Founding Lead Engineer / Principal Systems Architect based in the United States.
This is a foundational engineering role responsible for designing and building a next-generation evidence-governed AI and data platform from the ground up. The work sits at the intersection of distributed systems, data architecture, and applied AI in high-trust, regulated environments such as healthcare integrity and compliance-heavy domains. You will operate at both strategic and hands-on levels, translating abstract system concepts into production-grade software, scalable infrastructure, and validated workflows. The role demands deep technical ownership, from data modeling and service design to model integration and secure deployment. You will collaborate closely with a concept architect to shape system architecture in real time and rapidly turn ideas into working prototypes. This is a high-impact, founding-level opportunity to define core technical foundations that will scale across multiple regulated industries. The environment is fast-moving, ambiguous, and deeply engineering-driven, with strong emphasis on correctness, auditability, and security.
- Translate high-level system concepts into concrete architectures, including service maps, APIs, schemas, and implementation roadmaps.
- Design and build backend systems in Python, including APIs, data pipelines, orchestration layers, and distributed services.
- Develop identity resolution, entity linking, evidence management, and audit-ready data systems.
- Architect relational, graph, and retrieval-based data layers supporting complex, high-integrity workflows.
- Implement LLM integration layers including model routing, structured outputs, evaluation, and validation systems.
- Build deterministic, auditable workflows for regulated-domain decisioning and reporting.
- Create prototypes for internal review systems, visualization tools, and human-in-the-loop workflows.
- Lead infrastructure design using Kubernetes, CI/CD, observability, and secure deployment practices.
- Establish engineering standards for testing, documentation, validation, and system reliability.
- Build benchmarking, regression testing, and data quality validation frameworks.
- 8–12+ years of software engineering experience or equivalent exceptional technical background.
- Expert-level Python development experience in production environments.
- Strong background in backend systems, distributed architectures, and API design.
- Experience with relational databases (ideally PostgreSQL) and complex data modeling.
- Familiarity with graph systems, entity resolution, or knowledge graph design.
- Hands-on experience integrating LLMs or building AI-driven systems with structured outputs.
- Strong DevOps and infrastructure experience (Docker, Kubernetes, CI/CD, secure deployments).
- Experience with data validation, audit logging, RBAC, and secure system design principles.
- Ability to translate ambiguous system concepts into scalable technical solutions.
- Strong communication skills and comfort working closely with non-engineering stakeholders.
- Experience in regulated industries (healthcare, finance, government, cybersecurity) is highly valued.
- Competitive compensation aligned with seniority and experience.
- Equity or founding-team participation opportunities for exceptional candidates.
- Fully remote or hybrid flexibility depending on preference.
- Comprehensive medical coverage options with strong employer contribution.
- Self-managed PTO with minimum encouraged time off for work-life balance.
- Opportunity to work on high-impact, mission-critical AI systems in regulated domains.
- Direct influence over core system architecture and technical direction from day one.
- Exposure to advanced AI, distributed systems, and infrastructure challenges at scale.