Full-Stack Developer

Clera connects exceptional engineering talent with early-stage startups building AI-native products, scalable SaaS, and consumer applications. We represent engineers who ship quickly, influence product direction, and work directly with founders and product teams. Opportunities are with a cohort of vetted early-stage companies; specific role details and locations vary by client.

We are seeking Full-Stack Developers who deliver end-to-end features and take ownership across the stack. Successful candidates balance pragmatic engineering with product focus, shipping reliable, user-facing functionality that integrates AI where appropriate.

What you will do

• Own design and delivery of end-to-end features: API design, data modeling, frontend implementation, and production deployment.
• Ship polished user experiences with attention to usability, performance, and maintainability.
• Integrate AI capabilities (e.g., LLMs, RAG, embeddings, tool-calling) into product workflows and make intelligence reliable for end users.
• Design and implement backend services, data schemas, and operational tooling (CI/CD, monitoring, testing).
• Collaborate closely with founders, product, and design to define success metrics, prioritize work, and iterate based on user feedback and telemetry.
• Participate in architecture and roadmap discussions and make pragmatic trade-offs appropriate for early-stage growth.

Minimum qualifications

• 2–8 years of professional software engineering experience with a track record of shipping user-facing or backend products.
• Proficiency across the stack: TypeScript with React (or similar) on the frontend and Python or Node.js on the backend.
• Experience with relational or NoSQL databases (e.g., PostgreSQL) and familiarity with cloud platforms (AWS, GCP, or equivalent).
• Practical, production-level experience deploying or integrating LLMs or other AI services (engineering-focused).
• Comfort working in small teams with limited process and high ambiguity; ability to move fluidly between frontend, backend, and operations tasks.

Preferred qualifications

• Experience with retrieval-augmented generation (RAG), vector databases, embeddings, or retrieval pipelines.
• Familiarity with agent/workflow orchestration frameworks or tools (e.g., Temporal, LangGraph) and multi-agent systems.
• Experience building automated tests, evaluation pipelines, and monitoring for AI systems to ensure reliability beyond prototypes.
• Background building multi-tenant or enterprise-ready systems or working in regulated industries (healthcare, fintech, legal).

What successful candidates value

• Ownership: delivering end-to-end features from data model to production and monitoring.
• User-centric engineering: building maintainable code that solves measurable user problems.
• Pragmatic architecture: choosing practical solutions that accelerate impact in an early-stage environment.
• Continuous learning: adopting tools and practices that improve speed without sacrificing reliability and safety.

Location and role format

• Opportunities vary by client and may be remote, on-site, or hybrid. Specific location and workplace expectations depend on the hiring company.

Interview process (typical)

• Screening conversation to assess fit, communication, and interest in AI-driven product work.
• Technical deep-dive on architecture and system design for real-world AI problems.
• Coding or pairing session to evaluate practical engineering and product delivery skills.

Clera represents engineers to early-stage startups and prioritizes a candidate-first experience that lets you focus on technical fit and product impact.