We are looking for a Full-Stack Software Engineer who has hands-on experience building scalable, user-centric products and is excited about integrating AI technologies into real-world applications. In this role, you will work across the stack-frontend, backend, and infrastructure-to design, develop, and ship features that leverage cutting-edge AI, including voice-based interfaces and intelligent automation.

If you enjoy crafting clean code, solving complex problems, and experimenting with AI tools (LLMs, speech recognition, vector databases, etc.), we'd love to talk to you.

Key Responsibilities :

- Build and maintain end-to-end product features across the frontend, backend, and infrastructure.

- Integrate and optimize AI models, including LLMs, embeddings, speech-to-text, and other ML services.

- Strong knowledge of LLMs, prompt engineering, RAG, LLM evaluations/ monitoring.

- Architect scalable backend services and APIs using Node.js, Python, or similar technologies.

- Collaborate with founders and team to ship high-impact product experiences.

- Develop voice-enabled features (voice search, conversational UI, automated agents)

- Voice AI experience is a plus.

- Implement reliable dev-ops practices : CI/CD, monitoring, cloud deployments (AWS/GCP/Azure).

- Write clean, testable code and participate in code reviews.

- Troubleshoot and optimize performance across the stack.

- Passion for pushing the boundaries of AI and a commitment to staying at the cutting edge of industry trends and technologies.

Required Qualifications :

- 4+ years of professional full-stack development experience.

- Strong proficiency in Node.js, Python, or both.

- Experience with React, Next.js, or a modern frontend framework.

Hands-on experience working with AI/ML tools, such as :

- OpenAI / Anthropic / Llama APIs

- Vector databases (Qdrant, Pinecone, Weaviate, FAISS)

- Embeddings, retrieval pipelines (RAG)

- Experience developing RESTful APIs or GraphQL services.

- Experience designing and implementing event-driven architectures or microservices.

- Solid understanding of databases : PostgreSQL, MongoDB, Redis, etc.

- Experience with cloud environments (AWS, GCP, or Azure).

- Strong understanding of modern engineering best practices (testing, CI/CD,monitoring).

Preferred Qualifications (Nice-to-Have) :

- Experience building or integrating Voice AI applications :

- Speech-to-text (Whisper, AssemblyAI, Deepgram, Google Speech)

- Text-to-speech (ElevenLabs, Azure TTS, Amazon Polly)

- Voice assistants, IVRs, conversational agents

- Experience with containerization (Docker, Kubernetes).

- Familiarity with LLM fine-tuning, prompt engineering, or agent frameworks.

- Exposure to MLOps tools and workflows.