AI Engineer

• Design and implement LangGraph-based agent architectures with multi-turn memory, real-time decision-making, and complex state management.
• Build autonomous voice agents that handle interruptions, context switching, and live customer interactions.
• Develop specialized agent types (customer service, sales, routing) with intelligent tool and function calling capabilities.
• Implement agent evaluation systems using LLM-as-Judge methodologies to assess accuracy, hallucination detection, and goal achievement.
• Create configurable templates for rapid, multi-tenant deployment and scalability.
• Integrate and optimize LLM providers (OpenAI GPT-4o/GPT-5, Groq Llama 4, Anthropic Claude) with dynamic model routing and fallback strategies.
• Apply advanced prompt engineering techniques for voice-first applications, including templating, few-shot learning, and context management.
• Build streaming LLM pipelines that coordinate sentence-level text generation with real-time text-to-speech synthesis.
• Develop function calling frameworks for tools like call transfer, conferencing, recording, and external integrations.
• Build real-time speech-to-text pipelines using Deepgram Nova-3 with voice activity detection and interruption handling.
• Implement multi-provider text-to-speech orchestration (ElevenLabs, Deepgram, Cartesia) with voice cloning and tone control.
• Develop low-latency audio streaming over WebSockets with buffering, codec handling, and error recovery.
• Create dual-channel recording systems with speaker separation for QA and data collection.
• Optimize end-to-end latency in the STT → LLM → TTS pipeline to achieve natural conversational flow.
• Extend agents to handle text, voice, and vision inputs using GPT-4o multimodal capabilities.
• Build cross-modal reasoning systems that combine transcription, context, and visual data.
• Implement document and image understanding features for real-time reference during conversations.
• Design evaluation frameworks to assess multimodal performance and interaction quality.
• Architect event-driven microservices using NATS JetStream for reliable message delivery.
• Build multi-tenant RPC frameworks with access controls, secrets management, and isolation.
• Deploy to Kubernetes with autoscaling, health checks, and fault-tolerant design.
• Implement observability solutions using OpenTelemetry for full pipeline visibility.

Senior AI Engineer – Voice Agent Platform

GenAI Engineer

AI Engineer, MLOps, Fine Tuning