AI Engineer (Mid-Level)
clera
This is a solid early-career move if you want to own real production work instead of training projects. You'll ship AI systems that actually solve problems in healthcare, legal, and fintech—not toy examples. At a pre-seed startup, you'll work close to founders and see your code directly impact users.
Day-to-day: you'll design and maintain agentic systems that handle complex, multi-step workflows. You'll build retrieval-augmented generation (RAG) pipelines with vector databases and embeddings, implement multi-agent orchestration, and write evaluation infrastructure to catch regressions. This is full-stack AI work—APIs, data models, and enough depth to teach you how production LLM systems actually work.
This fits you if you have solid fundamentals in Python, familiarity with LLM frameworks and vector databases, and a portfolio showing you've built at least one end-to-end project. Computer science, math, or physics backgrounds help. You don't need years of experience—you need curiosity and the ability to learn fast.
To apply, submit your resume and a link to your GitHub or portfolio via CareerJumpShip. Include any projects involving LLMs or ML infrastructure.
About this role
ABOUT THE ROLE Join a fast-moving, pre-seed-backed AI startup building the next generation of agentic systems that automate complex, multi-step workflows across regulated and enterprise domains — including healthcare, legal, fintech, logistics, and compliance. As a mid-level AI Engineer on the core product team, you'll own production LLM-based services end-to-end, collaborate closely with founders and product, and ship features that deliver measurable impact for real users. WHAT YOU'LL DO - Design, build, and maintain agentic systems that automate complex, multi-step workflows across regulated industries. - Own production retrieval-augmented generation (RAG) pipelines and retrieval infrastructure, including vector databases, embeddings, and indexing for domain-specific search at scale. - Implement multi-agent orchestration, tool-calling, memory, and reasoning components to deliver robust AI-driven user experiences. - Develop evaluation and safety infrastructure to measure model performance, surface regressions, and enforce enterprise-level trust and reliability. - Ship full-stack AI products from MVP to enterprise-grade — designing APIs and data models, writing frontend and backend code, and operating production systems with CI/CD, monitoring, and testing. - Collaborate with founders, product, and design to prioritize work, define success metrics, and iterate based on user feedback and telemetry. WHAT WE'RE LOOKING FOR Must-haves: - 2–8 years of software engineering experience with demonstrated delivery of shipped user-facing or backend products. - Practical experience deploying LLMs or LLM-based services in production, including prompt design, orchestration, and tool integration. - Proficiency across the stack: Python plus TypeScript/React (or equivalent), cloud platforms (AWS or GCP), and relational or NoSQL databases. - Working knowledge of RAG patterns, vector databases, embeddings, and retrieval pipelines, with sound judgment on when to apply each approach. - Experience building automated tests, evaluations, and monitoring for AI systems to ensure reliability beyond demos. - Experience designing API-driven, high-throughput systems and real-time product features. Nice-to-haves: - Experience with agent or workflow frameworks (e.g., LangGraph, CrewAI) and orchestration tools (e.g., Temporal, Trigger). - Familiarity with fine-tuning, parameter-efficient tuning, or multi-modal model integration. - Background building multi-tenant or enterprise-ready systems, or prior experience in regulated industries such as healthcare, fintech, or legal. COMPENSATION & BENEFITS - Salary: $180,000 – $400,000 USD annually (reflecting a wide band across base and equity depending on experience). - Early-stage equity in a venture-backed startup.