Conversational AI Tech Lead
New
J
JobgetherConversational AI
Based in IndiaFull-TimeLead
Salary not disclosed
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Job Details
- Languages
- Excellent English communication skills
- Required Skills
- PythonSQLJavascriptTypeScriptNosqlRESTful APIs
Requirements
- Strong professional experience in Conversational AI, with hands-on expertise across LLMs, Agentic AI, and NLU-based systems.
- Proven experience as a Tech Lead, Engineering Manager, or in a comparable technical leadership position.
- Degree or professional background in Computer Science, Software Engineering, or a related discipline.
- Deep understanding of AI engineering, LLM application development, and production deployment.
- Practical experience with Speech-to-Text, Text-to-Speech, voice technologies, and telephony systems.
- Strong proficiency in API integrations including REST APIs, webhooks, and OAuth.
- Hands-on prompt engineering experience and ability to design knowledge structures for conversational systems.
- Strong programming skills in Python, JavaScript, and/or TypeScript, with familiarity with JSON and YAML.
- Experience using SQL and/or NoSQL databases.
- Excellent English communication skills for explaining complex concepts to diverse stakeholders.
- Strong technical documentation skills for architecture, configurations, and deployment processes.
Responsibilities
- Lead, mentor, and develop a team of Conversational AI Engineers, fostering a collaborative, high-performance culture.
- Provide hands-on technical leadership across the design, development, testing, and deployment of complex conversational AI solutions.
- Define robust technical architectures, assess feasibility and constraints, and evaluate APIs, integrations, and platform capabilities.
- Engineer and optimize prompts while integrating LLMs, Agentic AI, NLU models, and external platforms.
- Design and optimize speech technology solutions including STT, TTS, and telephony integrations.
- Conduct code reviews and architecture audits to ensure standards, security, scalability, and production readiness.
- Manage sprint activities, resolve technical blockers, and support the successful delivery of technical milestones.
- Establish AI governance, guardrails, and evaluation practices to support production stability.
- Build reusable technical components and intellectual property to improve delivery efficiency.
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