Clera
AI Engineer (Mid-Level)
RemoteUnited States only
- Role
- AI / ML
- Experience
- Mid
- Employment
- Full-time
- Company size
- Startup
$180k–$400k/yr
Check eligibility
Open to US only. Set where you work from to check your eligibility.
No BS summary
Mid-level AI Engineer needed for an AI startup building agentic systems for regulated industries. Must have 2-8 years of software engineering experience, production LLM deployment experience, proficiency across Python/TypeScript/React, cloud platforms (AWS/GCP), and databases. Experience with RAG, vector databases, and AI system testing is required.
Core skills
RAGLLMsagentic systems
Required skills
PythonTypeScriptReactAWSGCPvector databasesembeddingsindexingprompt designorchestrationtool integrationautomated testsevaluationsmonitoringAPI designrelational databasesNoSQL databases
Optional skills
LangGraphCrewAITemporalTriggerfine-tuningparameter-efficient tuningmulti-modal model integrationmulti-tenant systems
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.
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 they require
- 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.
- 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.
Benefits
- Early-stage equity in a venture-backed startup.
A fast-growing fintech startup building modern banking infrastructure for global businesses and AI-powered financial operations.
$180k–$400k/yr