Applied AI Field Engineer
$155,000–$190,000 year
On-siteCharlotte, North Carolina, United States
Job Summary
Design and build AI-powered features using large language models, prompt architectures, and retrieval-augmented generation pipelines to compress engineering labor. Integrate LLM APIs such as Anthropic Claude and OpenAI into production systems while managing tradeoffs across latency, cost, and performance. Partner with software engineers, QA engineers, and the lead engineer to define evaluation criteria, test benchmarks, and iterate on non-deterministic outputs. Engage directly with operating companies to validate workflows, participate in field-based hackathons, and prototype solutions that inform platform development.
Required Qualifications
- 4+ years of experience in software engineering, applied AI, or machine learning development
- Strong programming skills in Python and/or JavaScript
- Hands-on experience working with LLM APIs such as Anthropic Claude, OpenAI, or similar
- Experience designing and implementing prompt architectures and prompt engineering techniques
- Experience building retrieval-augmented generation pipelines and working with vector databases
- Familiarity with agent orchestration frameworks and multi-step AI workflows
- Experience integrating AI capabilities into applications via APIs and backend systems
- Strong understanding of handling structured and unstructured data in AI systems
- Ability to evaluate, debug, and improve non-deterministic AI outputs
- Experience working in a fast-paced, product-oriented development environment
- Strong problem-solving skills and ability to operate in ambiguous, evolving contexts
- Ability to collaborate closely with engineers, product managers, and QA within a pod structure
- Excellent communication skills and ability to explain technical concepts clearly
- Curiosity and willingness to learn domain-specific workflows, particularly within engineering and AEC contexts
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