AI Engineer – Conversational AI (End-to-End Product Ownership)

Job Summary:

AI Engineer

This is a cross-functional role that requires strong technical expertise in AI/ML, NLP, and system design, along with a product mindset and execution capability.

Key Responsibilities:

• Own the full product lifecycle

  of conversational AI tools—scoping, designing, building, testing, deploying, and maintaining solutions.
• Architect and implement voice bots and chatbots that interact naturally and contextually with users.
• Build and fine-tune

  NLP, NLU, LLMs, and RAG pipelines

  for voice and text interactions.
• Work with

  speech recognition (ASR)

  and

  text-to-speech (TTS)

  systems for real-time call automation.
• Integrate with

  telephony platforms (e.g., Twilio, Dialpad, Exotel)

  and messaging platforms (e.g., WhatsApp, Web, Messenger).
• Handle backend architecture, data flows, error handling, logging, performance monitoring, and latency optimization.
• Collaborate with product, design, and business teams to define and refine user flows and technical requirements.
• Deploy models in production using best practices in CI/CD, DevOps, and cloud platforms.
• Continuously monitor system performance, user feedback, and iterate based on data-driven insights.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, AI/ML, or related discipline.
• 3–6 years of experience in building and deploying production-grade AI/NLP applications.
• Proven experience in managing

  end-to-end AI product development

  —not just model-building.
• Strong programming skills in Python; experience with frameworks like PyTorch, TensorFlow, Hugging Face Transformers, LangChain.
• Solid experience with

  LLMs (e.g., GPT, Claude, Mistral)

  and deploying RAG-based architectures.
• Hands-on experience with

  voice tech

  : speech-to-text, TTS, telephony APIs, SIP/RTP protocols.
• Experience with

  cloud platforms (AWS, GCP, or Azure)

  and deployment pipelines (CI/CD, Docker, Kubernetes).
• Ability to write scalable, maintainable, and well-documented code.
• Strong understanding of backend systems and API integration.

Nice to Have:

• Familiarity with chatbot frameworks (Dialogflow, Rasa, Botpress, etc.)
• Experience with vector databases (Pinecone, Weaviate, FAISS) and embeddings.
• Experience working in a fast-paced startup environment.
• Strong product thinking and ability to prioritize trade-offs between tech and business needs.
• Experience with analytics tools and observability platforms for real-time monitoring.

What We Offer:

• Competitive compensation and ESOPs
• Opportunity to lead impactful products in the rapidly growing conversational AI space
• Flexible remote/hybrid work environment
• Autonomy, ownership, and support to bring your ideas to life
• Exposure to cutting-edge AI technologies and scalable systems

How to Apply:

AI Engineer – Conversational AI