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Engineering Manager – Forward Deployed Engineering
Blue Machines AI. Manage and mentor a team of Forward Deployed Engineers .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in managing and mentoring engineering teams while driving execution and delivering high-quality technical solutions. Proficient in system design, architecture, and leading complex projects in AI and automation across enterprise environments.
Highest-signal resume keywords
Engineering ManagementSystem DesignAI AgentsVoice AIWorkflow Automation
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software EngineeringDebuggingTroubleshootingProduction Systems DesignArchitecture ReviewTechnical Project LeadershipAI-Powered WorkflowsEnterprise IntegrationsCustomer-Facing EngineeringDistributed Systems
Soft Skills
Excellent CommunicationMentoringTeam BuildingAccountabilityCollaboration
Tools & Technologies
CRM IntegrationsTelephony PlatformsKnowledge Retrieval SystemsAgent OrchestrationCustomer Support Systems
Industry Keywords
Contact Center TechnologiesEnterprise SaaS PlatformsSolutions EngineeringAutomation OpportunitiesEngineering Operational Processes
Tech Stack
Tools & technologiesDistributed Systems
About the role
Key responsibilities & impact- 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
Requirements
What you’ll need- 8+ years of software engineering experience
- 2+ years of engineering management or technical leadership experience
- Strong hands-on engineering background
- Experience designing and operating production systems
- Strong system design and architecture skills
- Strong debugging and troubleshooting capability
- Experience leading engineers through complex technical projects
- Excellent communication skills
- Experience in one or more of: AI Agents, LLM Applications, Voice AI, Conversational AI, Contact Center Technologies, Workflow Automation, Enterprise SaaS Platforms, Customer-Facing Engineering, Solutions Engineering, Distributed Systems (strongly preferred)
Benefits
Comp & perks- Work at the frontier of AI and Voice AI
- Solve meaningful business problems using AI Employees
- Work directly with enterprise customers
- Lead high-impact deployments
- Influence architecture, product direction, and engineering culture
- Help define the future of AI-powered work