Founding Engineer

We are looking for a Founding Engineer with strong backend and AI expertise to join our early-stage product team. The ideal candidate should be hands-on with backend engineering and have a strong understanding of generative AI, LLMs, AI agents, and agentic AI systems. As a founding engineer, you will work closely with the founding team to design, build, and scale core product features from the ground up. You will have significant ownership and will be involved in technical architecture, product decisions, and engineering execution.

Responsibilities:

• Design and develop scalable backend systems, APIs, and microservices.
• Build AI-powered features using LLMs and generative AI.
• Design and develop AI agents and agentic AI workflows.
• Integrate and work with different LLMs such as OpenAI, Anthropic, Gemini, Llama, etc.
• Work with AI tools, frameworks, and APIs to build intelligent applications.
• Develop RAG (Retrieval-Augmented Generation) pipelines and work with vector databases.
• Implement prompt engineering, tool calling, function calling, structured outputs, and AI workflows.
• Build systems where AI agents can interact with APIs, databases, tools, and external services.
• Evaluate LLM/agent performance, accuracy, latency, and cost.
• Design reliable backend architecture for AI applications.
• Work with databases such as PostgreSQL, MySQL, MongoDB, Redis, etc.
• Deploy and scale applications using AWS / GCP / Azure.
• Collaborate closely with product and founding teams to convert ideas into production-ready solutions.
• Take end-to-end ownership of features from ideation, architecture development, and deployment.

The core requirements for the job include the following:

Backend Engineering:

• Strong experience in Python, Java, Go, or Node.js .
• Strong understanding of REST APIs, microservices, distributed systems, and system design.
• Experience with relational and/or NoSQL databases.
• Good understanding of cloud platforms, Docker, Kubernetes, CI/CD, and production systems.

AI / GenAI:

• Strong understanding of LLMs and generative AI.
• Hands-on experience with OpenAI / Anthropic / Gemini / Llama or similar LLM APIs.
• Understanding of AI agents and agentic AI architecture.
• Experience with frameworks/tools such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar.
• Knowledge of RAG, embeddings, vector databases, semantic search, and knowledge retrieval.
• Understanding of prompt engineering, function/tool calling, context management, and structured outputs.
• Familiarity with evaluating and monitoring AI applications.

Good to Have:

• Experience building an AI-first SaaS/product from scratch.
• Experience working in an early-stage startup or founding engineering team.
• Knowledge of MCP (Model Context Protocol) and AI tool integrations.
• Experience with AI coding/development tools such as Cursor, Claude Code, GitHub Copilot, or similar.
• Experience with LLM fine-tuning, model evaluation, or inference optimization.
• Strong product mindset and ability to work with ambiguity.