AI Engineer – Voice AI / Autonomous Agents

AI Engineer – Voice AI / Autonomous Agents

Who are we?

We are Spyne, redefining how cars are marketed and sold with cutting-edge Generative AI. What started as a bold idea—using AI-powered visuals to help dealers sell online faster—has evolved into a full-fledged AI-first automotive retail ecosystem.

Backed by $16M in Series A funding from Vertex Ventures, Accel, and other top investors, we’re scaling fast:

✔ Expanded across the US & EU markets

✔ Launched industry-first AI-powered Image & 360 solutions

✔ Achieved a 5X revenue surge in 15 months, aiming for 3-4X growth this year

Now, we’re rolling out an end-to-end GenAI Automotive Retail Suite and pushing into the US market to bring our AI-driven products to 3,000-4,000 dealers.

👉 Read more about us:

• Studio AI Product - t.ly/t0Ko5
• Retail AI Product - t.ly/EyKC9
• Series A Announcement -
• Spyne raises $16 Mil!
• Spyne raising another round!!
• Spyne secures funding for US Expansion!

What are we looking for?

We are looking for a Senior AI Engineer – Voice AI / Autonomous Agents to own and build Spyne’s in-house voice bot stack. This is a high-impact individual contributor role at the intersection of LLMs, ASR/TTS, and voice UX, focused on creating deeply human, latency-optimized conversations between auto dealerships and their customers.

📍 Location: Gurugram (Work from Office, 5 days a week)

🛠️ What will you do?

• Voice AI Stack Ownership: Build and own the end-to-end voice bot pipeline — ASR, NLU, dialog state management, tool calling, and TTS — to create a natural, human-like conversation experience.
• LLM Orchestration & Tooling: Architect systems using MCP (Model Context Protocol) to mediate structured context between real-time ASR, memory, APIs, and the LLM.
• RAG Integration: Implement retrieval-augmented generation to ground responses using dealership knowledge bases, inventory data, recall lookups, and FAQs.
• Vector Store & Memory: Design scalable vector-based search for dynamic FAQ handling, call recall, and user-specific memory embedding.
• Latency Optimization: Engineer low-latency, streaming ASR + TTS pipelines and fine-tune turn-taking models for natural conversation.
• Model Tuning & Hallucination Control: Use fine-tuning, LoRA, or instruction tuning to customize tone, reduce hallucinations, and align responses to business goals.
• Instrumentation & QA Looping: Build robust observability, run real-time call QA pipelines, and analyze interruptions, hallucinations, and fallbacks.
• Cross-functional Collaboration: Work closely with product, infra, and leadership to scale this bot to thousands of US dealerships.

🎯 What will make you successful in this role?

• Architect-level thinking: You understand how ASR, LLMs, memory, and tools fit together — and can design modular, observable, and resilient systems.
• LLM Tooling Mastery: You’ve implemented tool calling, retrieval pipelines, function calls, or prompt chaining across multiple workflows.
• Fluency in Vector Search & RAG: You know how to chunk, embed, index, and retrieve — and how to avoid prompt bloat and token overflow.
• Latency-First Mindset: You debug token delays, know the cost of each API hop, and can optimize round-trip time to keep calls human-like.
• Grounding > Hallucination: You know how to trace hallucinations back to weak prompts, missing guardrails, or lack of tool access — and fix them.
• Prototyper at heart: You're not scared of building from scratch and iterating fast, using open-source or hosted tools as needed.

🔧 What you must have

• 5+ years in AI/ML or voice/NLP systems with real-time experience
• Deep knowledge of LLM orchestration, RAG, vector search, and prompt engineering
• Experience with MCP-style architectures or structured context pipelines between LLMs and APIs/tools
• Experience integrating ASR (Whisper/Deepgram), TTS (ElevenLabs/Coqui), and OpenAI/GPT-style models
• Solid understanding of latency optimization, streaming inference, and real-time audio pipelines
• Hands-on with Python, FastAPI, vector DBs (Pinecone, Weaviate, FAISS), and cloud infra (AWS/GCP)
• Strong debugging, logging, and QA instincts for hallucination, grounding, and UX behavior

Why Spyne?

• 🌍 Real-world AI impact at scale
• 🤝 A-Grade team that balances speed with technical depth
• 💼 High autonomy and visibility from Day 1
• 📈 Rapid growth = faster career acceleration
• 💻 MacBook + all the tools and compute you need
• 🎯 Flat structure, no BS, just real work