Founding Engineer

Responsibilities:

• Own the design, development, and scaling of backend systems and core product architecture.
• Build highly scalable, reliable, and low-latency backend services and APIs.
• Design and develop microservices, distributed systems, and event-driven architectures.
• Build and integrate AI/ML, LLM, generative AI, and agentic AI capabilities into production products.
• Develop AI-powered workflows using LLMs, RAG, embeddings, vector databases, AI agents, and model APIs.
• Work on LLM orchestration, prompt engineering, evaluation, monitoring, and optimization.
• Design scalable data pipelines and backend infrastructure required for AI applications.
• Own technical decisions around architecture, databases, APIs, cloud infrastructure, and system design.
• Build production-grade systems with a strong focus on performance, scalability, security, reliability, and observability.
• Collaborate closely with founders, product, design, and business teams to convert product requirements into technical solutions.
• Take complete ownership of features from ideation, architecture development, deployment, and monitoring.
• Mentor engineers and contribute to establishing engineering best practices, coding standards, and development processes.
• Troubleshoot complex production issues and continuously improve system performance and reliability.
• Help shape the technical roadmap and engineering culture as the company scales.

Requirements:

• Strong programming experience in Python, Go, Java, or Node.js .
• Strong understanding of REST APIs, GraphQL, microservices, distributed systems, and system design.
• Experience designing and building scalable backend architectures.
• Strong knowledge of SQL and NoSQL databases such as PostgreSQL, MySQL, MongoDB, Redis, etc.
• Experience with Kafka, RabbitMQ, or other messaging/event-streaming systems.
• Hands-on experience building and deploying AI/ML or generative AI applications in production.
• Strong understanding of LLMs, RAG, embeddings, vector databases, prompt engineering, and AI agents.
• Experience working with models/APIs such as OpenAI, Anthropic, Gemini, Llama, Mistral, or similar.
• Experience with frameworks/tools such as LangChain, LlamaIndex, LangGraph, or similar.
• Understanding of LLM evaluation, hallucination reduction, model optimization, and AI observability.
• Experience integrating AI capabilities into backend/product systems. Strong experience with AWS, GCP, or Azure.
• Experience with Docker and Kubernetes.
• Knowledge of CI/CD, monitoring, logging, and production infrastructure.
• Experience building highly available and scalable cloud-native applications.
• Experience taking products from 0 to 1.
• Experience working in an early-stage startup environment.
• Experience with AI-first / SaaS / B2B products.
• Experience building agentic AI or autonomous workflows.
• Open-source contributions or strong technical community involvement.
• Experience hiring and mentoring engineering teams.