About the Role:

Our client is an AI-first B2B2C platform transforming the Real Estate industry. We build intelligent, agentic, and automated solutions that improve productivity, accelerate sales velocity, and enable data-driven decision-making for developers, channel partners, and homebuyers.

Key Responsibilities:

- Build and ship chat, voice, and multimodal AI agents integrated into production products.

- Design agent workflows using LLMs, tools, memory, and state.

- Implement voice pipelines, including ASR, TTS, turn-taking, and interruptions.

- Work on Indian language voice agents, including latency and quality tuning.

- Develop workflow automation logic driven by agents.

- Build task execution systems where agents plan, act, and verify outcomes.

- Design and implement media and martech agents as part of product features.

- Build persona-based systems for content, campaigns, and engagement.

- Implement agent moderation and control mechanisms.

- Add observability, logging, and debugging for AI behavior.

- Reduce hallucinations and failure modes through system design.

- Collaborate closely with product, design, and engineering teams.

Qualifications and Skills:

- Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science.

- Hands-on experience building LLM-powered applications.

- Experience with chat agents or conversational systems.

- Understanding of tool calling, agent loops, memory, and state.

- Experience integrating AI, APIs and MCP's into backend or product workflows.

- Familiarity with voice AI systems or strong interest in building them.

- Ability to rapidly prototype and iterate on AI-driven features.

- Strong debugging mindset for real-world AI failures.

- Comfort working in fast-moving product environments.

Strong plus if you have experience with:

- Voice agents, speech-to-text, text-to-speech, telephony systems, Indian language NLP or speech systems.

- Workflow automation or agent orchestration frameworks.

- RAG systems, embeddings, and vector databases.

- Martech, CLM, campaign automation, or ad-tech workflows.

- Persona-based content or personalization systems.

- SaaS products with real users and scale constraints.