Lead Forward Deployed Engineer
NewBe an early applicanthands-on individual contributor responsible for leading the design, development, and deployment of AI-enabled applications, intelligent automation, and integrated digital solutions that address complex business and operational challenges. The role works closely with business and technology stakeholders to translate requirements into scalable, reliable solutions using LLMs, document intelligence, APIs, workflow automation, RPA, data engineering, and cloud technologies. The role provides end-to-end technical ownership from rapid prototyping and solution design through integration, deployment, evaluation, and continuous improvement, while providing technical guidance and promoting effective engineering practices.
- Design, build, and deploy AI-enabled applications using LLMs, prompt engineering, retrieval-augmented generation (RAG), agentic workflows, and evaluation frameworks to address business and operational requirements. |
- Develop document intelligence solutions using OCR and LLM-based extraction, classification, and validation to automate the processing of permit applications, contracts, compliance documents, and other operational records. |
- Design and implement API integrations connecting permit databases, CRM, finance/ERP, e-signature, payment gateways, government-facing systems, and other enterprise platforms using REST APIs and webhooks. |
- Build and orchestrate end-to-end automated workflows using platforms such as n8n, Zapier, Make, Airflow, or custom Python services, including appropriate routing, approvals, notifications, and exception handling. |
- Develop RPA solutions to automate activities within legacy systems, external portals, and applications where API-based integration is unavailable or impractical. |
- Develop Python-based services, scripts, data-processing components, and LLM orchestration solutions using appropriate frameworks or direct API integrations. |
- Design and maintain SQL databases, data models, and data pipelines to transform permit, contract, inspection, compliance, and operational data into reliable structured datasets. |
- Build lightweight internal applications, dashboards, and user interfaces that enable business users to interact with automated workflows, review outputs, manage exceptions, and access operational insights. |
- Apply Git-based version control, testing, and CI/CD practices to support controlled, repeatable, and reliable development and deployment. |
- Deploy and operate AI, automation, integration, and data solutions on AWS, Azure, or GCP, applying appropriate monitoring, logging, configuration, and error-handling practices. |
- Develop reporting and visualization solutions that convert operational data into actionable information for business users and decision-makers. |
- Rapidly prototype and iterate technical solutions with business users, prioritizing working solutions, early validation, and continuous improvement while maintaining appropriate engineering standards. |
- Work directly with business and operational stakeholders to understand processes, identify automation opportunities, translate requirements into technical solutions, and support successful adoption. |
- Evaluate solution performance, build test and evaluation datasets, identify failure modes, and continuously improve the accuracy, reliability, and scalability of deployed AI and automation solutions. |
- Apply technical judgment to determine the most appropriate combination of AI, APIs, workflow automation, RPA, data engineering, and custom development for each business problem. |