Senior AI Engineer, Conversational AI & Agentic Systems
New
J
JobgetherAI, Conversational Systems
USFull-TimeSenior
Salary250,000 - 300,000 USD per year
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Job Details
- Required Skills
- PostgreSQLPythonSQLWebRTCPrompt EngineeringLLM
Requirements
- Hands-on experience designing, building, and deploying production voice AI or real-time conversational AI systems.
- Experience with speech technologies including speech-to-text, text-to-speech, telephony systems, or streaming audio pipelines.
- Strong understanding of voice AI challenges such as latency optimization, interruptions, turn-taking, transcription accuracy, and conversation flow.
- Experience integrating real-time communication technologies such as Twilio, WebRTC, or similar platforms.
- Strong experience working with LLM APIs such as OpenAI, Anthropic, or comparable AI platforms.
- Deep understanding of prompt engineering, agent architectures, tool usage, retrieval systems, and AI workflow design.
- Ability to determine when to use agents, tools, retrieval-based approaches, or deterministic logic.
- Advanced Python programming skills, including asynchronous development with tools such as asyncio and related frameworks.
- Experience building APIs, backend services, and high-quality production software.
- Strong SQL skills, preferably with PostgreSQL, and experience designing data models and ETL workflows.
- Knowledge of AI system evaluation, testing strategies, observability, and reliability practices.
Responsibilities
- Design and build real-time conversational voice AI systems that support natural, effective user interactions.
- Develop AI orchestration frameworks, including agent workflows, state management, tool integration, and system handoffs.
- Architect and optimize pipelines involving speech-to-text, LLM reasoning, tool calling, and text-to-speech technologies.
- Evaluate and improve conversation design, prompt strategies, workflow architecture, latency, and interaction quality.
- Build resilient AI systems capable of handling ambiguity, interruptions, edge cases, and complex real-world conversations.
- Develop clean, tested, production-ready Python applications, APIs, backend services, and orchestration components.
- Create and maintain data pipelines that capture, process, and analyze insights from user interactions.
- Partner with engineering and product teams to define technical strategies and improve AI product capabilities.
- Contribute to AI system evaluation, monitoring, reliability improvements, and production optimization.
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