Lead AI Engineer

About the Role

We are looking for a passionate AI Engineer with 37 years of experience to design, build, and deploy AI-powered systems. The ideal candidate should have hands-on experience with Retrieval-Augmented Generation (RAG), Agentic AI frameworks, and multi-agent systems, along with strong backend engineering expertise.

You will work on building intelligent applications that leverage LLMs, autonomous agents, and scalable infrastructure to deliver production-grade AI solutions.

Key Responsibilities

• Design and implement AI-powered applications using LLMs and modern AI frameworks
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines
• Develop and orchestrate Agentic AI workflows and multi-agent systems
• Integrate LLMs with backend services, APIs, databases, and vector stores
• Develop scalable backend systems
• Optimize prompts, system design, and inference pipelines for performance and cost
• Deploy AI solutions to production environments (cloud-native preferred)
• Monitor, evaluate, and improve AI system performance
• Collaborate cross-functionally with product, design, and engineering teams

Required Skills & Qualifications

• 27 years of software engineering experience
• Strong proficiency in Python (preferred) or Node.js/TypeScript

Hands-on experience with:

• Retrieval-Augmented Generation (RAG)
• Vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus)
• Agent frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, etc.)
• Multi-agent orchestration systems
• Experience integrating and working with LLM APIs (OpenAI, Anthropic, open-source models)
• Solid backend experience (FastAPI, Django, Express, microservices)

OR

• Strong frontend experience (React, Next.js, AI-integrated UX systems)
• Understanding of embeddings, prompt engineering, evaluation techniques
• Experience deploying applications on AWS/GCP/Azure. AWS prefered
• Good understanding of system design and scalable architectures

Good to Have

• Experience building or integrating Voice AI stacks
• Speech-to-Text (Whisper, Deepgram, etc.)
• Text-to-Speech (ElevenLabs, Azure TTS, etc.)
• Real-time streaming pipelines
• Conversational voice agents
• Experience fine-tuning or working with open-source LLMs
• Experience with monitoring LLM performance and guardrails
• Knowledge of CI/CD and DevOps practices
• Experience building AI products in production environments

What Were Looking For

• Strong problem-solving and system-thinking mindset
• Ability to rapidly prototype and iterate AI solutions
• Product-oriented thinking
• Ownership mindset and ability to work in fast-paced environments