Blue Machines AI

Engineering Manager

• Lead and mentor the Forward Deployed Engineering team
• Establish a high-performance engineering culture
• Drive execution across multiple customer deployments
• Participate in hiring and team building
• Work directly with enterprise customers to understand workflows and identify automation opportunities
• Translate requirements into technical solutions and design AI-powered workflows
• Lead customer deployments from design to production
• Ensure successful adoption and measurable business outcomes
• Engage with CTOs, engineering leaders, product leaders, operations teams, customer support organizations, and business stakeholders
• Design and review solutions involving Voice AI, agent orchestration, workflow automation, enterprise integrations, knowledge retrieval systems, CRM integrations, telephony platforms, and customer support systems
• Review production code, conduct architecture reviews, debug production incidents, build prototypes, and solve complex technical problems
• Evaluate engineering tradeoffs and identify reliability and scalability risks
• Balance customer commitments with engineering capacity
• Prioritize across multiple deployments, identify delivery risks, manage scope and stakeholder expectations
• Lead production incident reviews and improve observability, debugging practices, reliability, and operational processes
• Build customer and engineering relationships, lead deployments, scale FDE processes, mentor engineers, and help define AI Employee deployment practices

Explore Engineering Manager – Forward Deployed Engineering (FDE) at Blue Machines AI. Review requirements and application details.

Engineering Manager – Forward Deployed Engineering (FDE)

• Manage and mentor a team of Forward Deployed Engineers
• Establish a high-performance engineering culture
• Drive execution across multiple customer deployments
• Help engineers navigate ambiguity and technical complexity
• Participate in hiring and team building
• Create an environment of accountability, ownership, and continuous improvement
• Work directly with enterprise customers to understand business workflows, identify automation opportunities, translate requirements into technical solutions, design AI-powered workflows, lead deployments from design to production, and ensure successful adoption and measurable outcomes
• Engage with CTOs, engineering leaders, product leaders, operations teams, customer support organizations, and business stakeholders
• Design and review solutions involving Voice AI, agent orchestration, workflow automation, enterprise integrations, knowledge retrieval systems, CRM integrations, telephony platforms, and customer support systems
• Review production code, conduct architecture reviews, debug production incidents, build prototypes, solve complex technical problems, evaluate engineering tradeoffs, and identify reliability and scalability risks
• Balance customer commitments with engineering capacity
• Prioritize across multiple deployments, identify delivery risks, manage scope and stakeholder expectations, and ensure predictable execution and delivery quality
• Lead production incident reviews, improve observability and debugging practices, drive reliability improvements, establish engineering operational processes, and create feedback loops that improve delivery quality
• Build customer and engineering relationships, understand the Blue Machines platform and deployment patterns, lead customer deployments, scale FDE processes, mentor engineers, and help define AI Employee deployment practices across industries

Explore Engineering Manager – Forward Deployed Engineering at Blue Machines AI. Review requirements and application details.