Senior AI Engineer, Backend

🚥 About Snapfix
Snapfix is on a mission to simplify the world's operations. We build the world's most user-friendly platform for managing maintenance, inspections, and daily operations through photos, messages, and checklists. Hotels, facilities, and teams across the globe rely on Snapfix to get things done, fast.
💻 The Role
You'll be the primary technical owner of AI at Snapfix, building the backend foundations and evaluation systems that make our AI reliable, useful, and scalable.
This is a hands-on individual contributor role. You'll write production code, shape architecture, and own AI quality from development through release and ongoing improvement. Working closely with Engineering, Product, and Customer teams, you'll turn user needs into practical capabilities and establish how we measure whether they work.
⚙️ What You'll Own
Scalable AI foundations: Build backend services, APIs, and reusable components that help engineers develop, test, and ship AI features consistently.
Flexible AI harnesses: Create modular, versioned interfaces for swapping and comparing models, providers, prompts, and orchestration frameworks without rewriting product features.
AI quality and evaluation: Define success with Product. Build representative datasets, automated evaluations, and human review workflows that measure task success, expose failures, and catch regressions before release.
Production reliability: Operate AI services on AWS with tracing, monitoring, alerts, and recovery mechanisms. Balance quality, latency, and cost as usage grows.
Secure, maintainable delivery: Build tests and evaluations into CI/CD, document key decisions, and protect customer data through access controls, output validation, and safeguards against prompt injection and unintended actions.
🎯 What We're Looking For
Senior backend experience: 5+ years building production systems, with strong foundations in API design, data modeling, asynchronous processing, and reliability. We're language agnostic.
Production LLM ownership: You've personally shipped and maintained LLM-powered features used by real users. You can explain your architectural decisions, what failed, and how you improved the system.
Evaluation experience: You've built repeatable AI evaluations and used their results to make release or improvement decisions. You understand how automated checks and human judgment work together.
Practical AI engineering: Experience integrating LLM APIs and implementing patterns such as structured outputs, retrieval, and tool calling. You can choose an approach based on the problem and explain its tradeoffs.
Operational depth: You've deployed and debugged services on AWS, using monitoring and production evidence to investigate problems and improve performance.
Independent judgment and clear communication: You can turn ambiguous requirements into manageable work, collaborate async across time zones, and explain technical choices to engineering and product colleagues.
💎 Nice to Have
Experience training or fine-tuning models and measuring improvements against a baseline.
Experience building shared AI infrastructure, provider integrations, or evaluation tooling used by other engineers.
🌍 Location
Remote within India, or based at Snapfix headquarters in Ahmedabad.

Work arrangement
No