Applied AI Engineer

What you'll be doing
We are hiring engineers with complementary strengths. Projects will be assigned based on each engineer’s experience.

1. Build internal AI services using open-weight language models for document processing, customer support and employee chat, replacing external APIs while preserving required functionality.
2. Connect models to company systems and approved data through APIs. Implement output validation, access controls, failure handling and fallback to approved providers.
3. Work with Infrastructure and DevOps teams to deploy models on company-controlled infrastructure. Improve response times, concurrent request capacity and serving costs using representative workloads.
4. Compare internal models with existing providers through repeatable quality, latency and cost evaluations. Use the results to guide model selection, prompts, retrieval and fine-tuning, and verify quality during staged rollouts.
5. Integrate internal models with coding assistants and agents that retrieve code, propose changes and run tests within approved permissions. Help teams adopt these tools through practical examples and training, preserving code-review and release requirements.
6. Track usage by business and service. Compare actual operating costs with estimated external-provider costs for the same workload, and measure workflow time saved after review and rework, alongside defect rates.