Forward Deployment Engineer - Frontier AI Deployments

Forward Deployment Engineer — Frontier Ai DeploymentsFunction: Forward Deployment Engineering / Applied AI Engineering / Model DeploymentRole Type: Forward Deployment Engineer / Customer-Embedded AI EngineerRole Summary:Accellor is looking for a Forward Deployment Engineer to work directly with strategic customers and help deploy frontier AI models into real production environments.This role combines hands-on software engineering, AI application development, solution design, customer collaboration, and production deployment. The engineer will understand customer problems, design practical AI solutions, build working systems, integrate with existing platforms, and drive adoption in production.The ideal candidate is a strong builder who can operate in ambiguous environments, move quickly, write high-quality code, and turn frontier AI capabilities into measurable business impact.Key Responsibilities:1. Customer Discovery & Technical ScopingWork directly with customer engineering, product, business, and domain teams to understand workflows, technical constraints, and high-value AI opportunities.Translate ambiguous customer problems into clear technical plans, success criteria, and delivery milestones.Identify where models can deliver measurable value in real production workflows.2. Solution Design & ArchitectureDesign AI-powered systems that integrate models with customer data, tools, APIs, applications, and security controls.Define practical architecture for model usage, retrieval, context management, tool calling, orchestration, evaluation, monitoring, and production reliability.Balance speed, quality, safety, cost, scalability, and maintainability.3. Hands-On Build & IntegrationBuild prototypes, production applications, APIs, integrations, internal tools, and workflow automation using models.Work closely with customer engineering teams to connect AI systems into existing enterprise platforms, data sources, identity systems, and business processes.Write reliable, maintainable code while moving quickly through evolving requirements.4. Production Deployment & AdoptionOwn the path from prototype to production, including testing, rollout planning, observability, reliability, and operational readiness.Ensure deployed systems are secure, usable, measurable, and aligned with customer success criteria.Drive adoption by working with users, operators, engineering teams, and leadership.5. Evaluation, Safety & ReliabilityDefine evaluation methods to measure model quality, grounding, accuracy, latency, cost, safety, and workflow impact.Build feedback loops that detect failures, improve outputs, reduce hallucinations, and maintain trust in production usage.Ensure deployments follow security, privacy, access control, compliance, and responsible AI expectations.6. Product & Research FeedbackCapture learnings from real customer deployments and share actionable feedback with Product, Research, Engineering, Safety, and GTM teams.Identify repeatable deployment patterns, product gaps, and opportunities to improve models and platforms.Help turn successful customer solutions into reusable technical patterns and deployment playbooks.