Senior Backend Engineer
Job Description
You’ll improve and scale our existing systems while designing new services end-to-end. You’ll collaborate across an international engineering team, mentor other engineers, and help set high standards for quality, reliability, and developer experience.\n\nResponsibilities\nOwn & evolve our backend: Improve performance, reliability, and maintainability of existing PHP and Python services (e.g. refactors, migrations, test coverage, resilience, cost/perf tuning).\nBuild new services & APIs: Design, implement, and operate secure, well-documented REST endpoints and event-driven systems that our mobile and web apps love.\nLay the AI foundations:\n1) Stand up data pipelines and storage for embeddings & retrieval (e.g.
vector indices, feature stores).\n2) Build RAG pipelines, prompt/response evaluation, guardrails, and model-orchestration layers.\n3) Integrate hosted LLMs and/or self-hosted inference as appropriate, with observability and cost controls.\nTechnical leadership: Lead projects, break down scope, make pragmatic build-vs-buy calls, and mentor engineers through reviews, pairing, and design docs.\nQuality & DevEx: Raise the bar on testing, CI/CD, observability, and documentation; champion secure-by-default patterns.\nCross-functional collaboration: Partner with Product, Design, and Customer teams to ship clear, practical solutions that users adopt quickly.\nDevOps: Contribute to infra as code, containerization, and runtime operations alongside our platform team.\n\nExperience and Skills\n5+ years building and operating production backend systems.\nPHP expertise and comfort picking up one or more of: Python, Go, or Node.js.\nSolid with relational databases (MySQL), caching (Redis), and queues/streams (e.g. SQS, Kafka).\nProven ability to design clean APIs, data models, and service boundaries; familiarity with event-driven and asynchronous patterns.\nHands-on with cloud platforms (AWS preferred), Docker, and CI/CD (e.g. GitHub Actions).\nExperience shipping AI-enabled features: LLM APIs, embeddings/vector stores, retrieval pipelines, prompt/tooling frameworks, evaluation/metrics.\nStrong fundamentals in testing, security, and privacy, plus practical monitoring/alerting (e.g.
Datadog).\nExcellent written and verbal communication; comfortable collaborating across time zones and working async.\nTrack record of mentoring or leading small squads.\n\nNice to have\nKubernetes and Terraform; cost/performance optimization at scale.\nDomain knowledge in maintenance/facilities or mobile-centric workflows.\nObservability for ML/LLM systems (quality, latency, cost, safety).\n\nLocation: This role can be remote within India or based in Ahmedabad at Snapfix headquarters.