Forward Deployed Engineer

# Forward Deployed Engineer ## Company Overview *Not specified.* ## Job Summary The **Forward Deployed Engineer** (FDE) plays a critical role in delivering customer-centric AI solutions by owning outcomes, integrating complex enterprise systems, and leading technical engagements. This role requires a blend of technical expertise, customer empathy, and leadership to ensure successful deployment and adoption of AI-driven products, ultimately contributing to the organization’s growth and customer satisfaction. ## Responsibilities - **Own Customer Outcomes:** Lead technical engagements with customers, ensuring successful deployment and operationalization of AI and agent-based systems, with a focus on delivering measurable business value. - **Build and Maintain Agent Systems:** Develop, fine-tune, and evaluate large language model (LLM)-powered or agent-based applications in production, understanding system failures, evaluation metrics, and optimization strategies. - **Full-Stack Engineering:** Design and implement solutions across the stack, including frontend dashboards, backend orchestration services, data pipelines, and deployment infrastructure, to support customer needs. - **Enterprise System Integration:** Integrate with enterprise systems such as SAP, Salesforce, Oracle, Snowflake, Databricks, or identity providers like Okta and Azure AD, ensuring robust, scalable, and compliant API connections. - **Customer Engagement & Communication:** Interact directly with customer stakeholders, including CTOs and operational teams, to gather requirements, provide technical guidance, and communicate progress and outcomes effectively. - **Mentorship & Team Leadership:** Lead small engineering teams, break down complex projects, set priorities, review code, and foster best practices to ensure high-quality deliverables. ## Qualifications - **Experience:** 3-7 years in software engineering, AI engineering, or applied machine learning, with at least 2 years in customer-facing roles owning outcomes. - **Technical Education:** Strong academic background in Computer Science, Engineering, or related fields; advanced degrees are a plus but not required. - **AI & ML Systems:** Hands-on experience building production agent systems, shipped at least one substantial LLM-powered or agent-based application in the last 18 months. - **Full-Stack Engineering:** Proficiency across frontend (TypeScript/JavaScript), backend, data engineering, and deployment infrastructure. - **Programming Skills:** Excellent Python skills, proficiency with ML frameworks like PyTorch, and familiarity with SQL, Bash, Docker, and Kubernetes. - **Enterprise Systems Integration:** Experience integrating with enterprise APIs (e.g., SAP, Salesforce, Snowflake) at an API depth, with a track record of production deployments. - **Customer-Facing Maturity:** Proven experience engaging directly with customers, managing expectations, and owning outcomes. - **Domain Knowledge:** Credible understanding of one or two industry domains such as healthcare, finance, logistics, or retail. - **Leadership & Communication:** Demonstrated ability to lead small teams, communicate effectively in writing and verbally, and foster collaboration. ## Preferred Skills - Experience with frameworks like LangGraph, LlamaIndex, or similar orchestration tools. - Familiarity with inference economics and model fine-tuning. - Experience with customer-facing applications using TypeScript/JavaScript. - Knowledge of enterprise security, compliance, and certification requirements. - Ability to handle non-determinism and system debugging in agent systems. ## Experience - 3 to 7 years of relevant experience in software/AI engineering. - At least 2 years in direct customer-facing roles, owning outcomes and managing stakeholder expectations. - Proven track record of shipping production AI applications, especially LLM-powered or agent-based systems. ## Environment - The role may involve in-office, remote, or hybrid work settings depending on the company's policies. - Work involves collaboration with cross-functional teams, customer engagement, and hands-on technical development. - The environment emphasizes a customer-centric, outcome-oriented approach with a focus on high-quality engineering practices. ## Salary *Not specified.* ## GrowthOpportunities *Not specified.* ## Benefits *Not specified.*