Lead Forward Deployed Engineer We are seeking a Lead Forward Deployed Engineer to join our team focused on developing AI agents, along with the backend and frontend for related applications. With 20+ agents launched, we accelerate innovation across critical industries. You'll work in a high-impact, high-autonomy environment, taking projects from concept to production. Responsibilities Collaborate with business stakeholders, product teams, and domain experts to understand requirements and translate them into practical technical solutions that drive measurable business outcomes Design and implement backend, full-stack applications, AI agents, and platform components, supporting rapid development and deployment of GenAI use cases Support delivery of solutions across the lifecycle - from prototyping through production rollout and iteration - ensuring reliability and usability in real-world environments Apply current LLM patterns such as RAG, retrieval, routing, tool-use, agent workflows, and evaluation approaches to deliver reliable and efficient AI systems Build and maintain developer tooling, CI/CD pipelines, and observability practices to support safe, fast, and stable iteration Follow strong engineering practices, including modularity, maintainability, and production readiness, while applying secure SDLC and privacy-by-design standards Contribute as a hands-on engineer within the team, supporting implementation, collaborating with peers, and helping resolve technical challenges Document and share learnings from implementations to contribute to team knowledge and incremental improvements in delivery practices Requirements 5+ years of professional software engineering experience contributing to delivery of production systems At least 1 year of relevant leadership experience Strong full-stack development skills with working knowledge of backend and frontend development Background in building AI agents using TypeScript, .NET, or Go Proficiency in cloud platforms such as AWS, Azure, or GCP, with a proven track record delivering secure, reliable, cloud-native systems Exposure to AI/LLM-based solutions (e.g., using APIs or basic RAG patterns) in practical implementations Basic knowledge or exposure to at least one business domain Capability to collaborate with stakeholders and translate business requirements into technical solutions Excellent problem-solving and communication skills, with ability to work effectively within a team Strong English communication skills (B2 level or higher) Nice to have Familiarity with LangChain, LangGraph, and MCP, along with vector/RAG systems and OpenSearch Expertise in evaluation frameworks and advanced LLM patterns (orchestration, tool use, fine-tuning, model adaptation) Exposure to machine learning workflows, including training, deployment, and monitoring Understanding of CI/CD, Infrastructure as Code, and observability practices Awareness of secure SDLC, privacy considerations, and regulatory or compliance standards (e.g., SOC 2, HIPAA)