Forward Deployed Engineer, Voice AI – Telephony

Blue Machines AI

. Design, prompt, build, and deploy production voice agents, including guardrails, conversation design, and tool-calling logic .

Posted 10/27/2026full-timeDelhi • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying production voice agents, integrating backend systems, and implementing AI frameworks. Proficient in analyzing performance metrics and optimizing agent interactions while maintaining strong client communication.

Highest-signal resume keywords

Voice Agent DevelopmentAI/LLM Application ExperiencePython or Java ProficiencyCloud Platform Experience (GCP)API and WebSocket Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Voice Agent DesignBackend IntegrationREST API DevelopmentSQL Data AnalysisAI Framework ImplementationRoot-Cause AnalysisPerformance OptimizationConversation DesignTool-Calling LogicData Pipeline Management

Soft Skills

Client-Facing CommunicationTechnical Workshop Leadership

Tools & Technologies

LangChainOpenAI APIsGCPOAuth2JWTWebSocketsTwilioAvayaSIPWebRTC

Industry Keywords

Conversational AIVoice AITelephony StacksReal-Time ProtocolsCRM Integration

Tech Stack

Tools & technologies

CloudGoogle Cloud PlatformJavaPythonSQL

About the role

Key responsibilities & impact

Design, prompt, build, and deploy production voice agents, including guardrails, conversation design, and tool-calling logic
Build scalable backend integrations using REST APIs, WebSockets, webhooks, callbacks, and CRM writes
Connect the Blue Machines platform with enterprise systems
Implement AI/LLM frameworks using LangChain, OpenAI APIs, or similar SDKs
Read system logs, traces, and call flows to perform root-cause analysis
Determine whether issues originate from prompt design, the platform layer, or data pipelines
Monitor and optimize agent metrics including completion rate, hallucination rate, latency, and cost
Run funnel experiments on conversation cadence
Partner directly with client engineering teams
Lead technical workshops and manage client expectations
Travel for live-call reviews and deployment reviews
Take full technical ownership of agent performance in production

Requirements

What you’ll need

4–6 years of software development experience
At least 2+ years of hands-on experience shipping live LLM/AI applications (agents, RAG, or chatbots; voice experience is a plus)
Proficiency in Python or Java for backend architecture and integration work
Hands-on experience with cloud platforms, preferably GCP
Deep knowledge of APIs, WebSockets, and authentication protocols (OAuth2, JWT)
Ability to pull and analyze data independently using SQL, Python, or Sheets
Strong client-facing communication skills with the ability to explain technical complexities in plain terms
Willingness to travel for on-site client workshops and deployment reviews
Nice to have: Knowledge of telephony stacks and real-time protocols (SIP, WebRTC, Twilio, Avaya, Ubona)
Nice to have: Experience with Voice AI or Conversational AI systems