Applied Intelligence · Lagos · Hybrid · Full-time
AI Engineer
Ship grounded assistants and document intelligence with evaluation, guardrails, and human accountability.
Mission
Enterprise AI
Enterprise knowledge that must not invent policy.
Assistants must be grounded, evaluable, and accountable—not demo theatre.
Responsibilities
- • Design retrieval and evaluation loops
- • Integrate assistants into secure product surfaces
- • Partner with security on redaction and access
- • Document failure modes and ownership
Required skills
- • Production experience with LLM applications
- • Evaluation mindset
- • API and data pipeline fluency
- • Clear risk communication
Preferred skills
- • Private/cloud inference ops
- • Vector stores
- • Document AI
What success looks like
Answers cite sources; refusals are deliberate; golden sets catch regressions before users do.
Experience · 3+ years building production ML/LLM systems
Technology · Python · RAG · Evaluation · TypeScript
Hiring process
- 01 Application — CV, links, and a short note on work you are proud of. We read carefully; we do not farm volume.
- 02 Initial Conversation — A human conversation about craft, motivations, and how we work—no trick questions.
- 03 Technical Discussion — Architecture and trade-offs on systems like yours. We care how you think.
- 04 Practical Exercise — Only where appropriate—time-boxed, respectful of your evenings, reviewed with feedback.
- 05 Team Conversation — Meet people you would build with. Culture fit means shared standards, not sameness.
- 06 Offer — Clear scope, expectations, and growth path. Questions welcome.
Apply
Submit your application for AI Engineer. Drafts auto-save in this browser.