Engineering Team Lead

Position Name - Engineering Lead (Founding Team)Location - Remote (India)Experience Range - 10+ yrsMandatory Requirement:Experience: 10+ years of hands-on systems or backend engineering, with 3+ years in a senior or lead role.Systems Thinker: You reason about distributed systems, failure modes and scalability trade-offs naturally. You build for production, not for demos.Technical Range: Strong in Python (primary) plus at least one of Go, Rust or Java. Solid command of PostgreSQL (or equivalent RDBMS) and Kafka or similar message brokers. Hands-on with Docker, CI/CD and cloud infrastructure (AWS / GCP / Azure). Workflow orchestration (Prefect, Airflow or equivalent) is a strong plus.Builder, Not Maintainer: Proven track record of building and shipping real-time or near-real-time data pipelines from scratch in production.Shipping Cadence: You ship working software weekly, keep Linear (or equivalent) honest day-to-day, and treat code review as part of the job.Startup DNA: You set the pace rather than wait for it. Ambiguity does not slow you down. You ship at 80% and learn from what breaks.About the client: Our client is AI startup backed by a NYC-based venture accelerator, keeps commercial fleets on the road by predicting failures weeks before they happen. They fuse telematics, sensor streams and repair logs with AI to cut breakdowns, lower repair costs and extend vehicle life across the $20B US market.Job Roles and Responsibilities:Carry customer-facing reliability: Own the SLAs to live fleet customers. When a pipeline drops, an alert misses or a dashboard breaks, you are the owner, not the escalation point.Cut customer onboarding from days to hours: Own the platform automation, stability and reliability that lets new fleet customers get value in their first week.Own real-time data pipelines end-to-end: Design and build the ingestion, processing and storage of telematics and sensor streams from commercial fleet vehicles. High-frequency, time-series, in production.Drive DevOps practices: CI/CD pipelines, Docker-based deployments, infrastructure automation, monitoring and observability.Lead integrations: Telematics and maintenance platforms (such as Geotab, Samsara, Motive, RTA, Fleetio) and third-party APIs.Productionize ML: Partner closely with the ML team to ship predictive models and automate maintenance alert pipelines from research code to production.Lead a small team, hands-on: Roughly 70% coding, 30% mentoring and planning. Mentor engineers on code quality and design standards. Run sprint planning, daily Linear hygiene and weekly demos of working software Experience:Background in IoT, telematics, vehicle data or any high-frequency sensor / streaming domain (industrial, logistics, fintech).Experience building third-party API integrations at scale.Familiarity with ML model deployment, time-series analysis or anomaly detection pipelines.Prior experience hiring or mentoring junior engineers through steep learning curves.

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