Top Tech Jobs & Startup Jobs in Delhi

Own enablement for Implementation and Customer Success teams by designing SOPs, curricula, onboarding, certification, QA frameworks, coaching systems, and continuous learning programs. Lead trainers and QA analysts, establish measurable capability standards, partner with Product and Operations on enablement, and use performance data to improve ramp time, process adherence, call quality, and product expertise.

Lead quality engineering vision and roadmap across product lines, drive CI/CD and release readiness, embed shift-left/shift-right practices, adopt AI-driven testing, mentor SDET managers, align quality metrics with executives, and architect test strategies for distributed systems and mobile.

Supports product marketing research, analytics reporting, competitor and customer research, customer education, product launches, campaigns, and presentations. The apprentice organizes and validates data, gathers industry benchmarks, assists with cross-functional projects, and develops familiarity with marketing, technology, SaaS, and business growth while working independently and meeting deadlines.

Owns company-wide revenue retention and add-on monetization analytics across CPaaS, AI features, Customer Success, and Finance. Builds canonical GRR, NRR, churn, and monetization metrics; applies causal inference methods to distinguish true retention drivers from bias and data artifacts; guides experimentation and forecasting; and influences cross-functional product, pricing, lifecycle, and customer success decisions without direct authority.

Owns customer growth analytics across onboarding, activation, trial-to-paid, multi-product adoption, retention, and expansion. The role develops canonical metrics, segment definitions, value models, and causal-inference standards; identifies behaviors that predict expansion; evaluates experiments; and translates product, behavioral, and revenue data into guidance for Growth, GTM, Finance, and product leaders. It also shapes event taxonomy, influences roadmap and investment decisions, and establishes reusable analytical practices across teams.

Own analytics and measurement for HighLevel’s AI product portfolio. Define instrumentation standards, feature-level KPIs, adoption and quality metrics, and rigorous approaches for evaluating nondeterministic AI features. Partner with experimentation leaders, PMs, engineering, and Analytics Engineering to close data gaps, influence product roadmaps, establish canonical metrics, and mentor future analysts.

Own the architecture health and resilience of HighLevel’s billion-scale distributed systems. Identify failure modes, capacity constraints, consistency risks, and cross-service dependencies; approve critical designs; prototype and ship architectural fixes; and improve backpressure, degradation, idempotency, and fault isolation. Partner across teams through design reviews, incident remediation, and postmortems while raising engineering standards for systems operating at massive scale.

Owns the platform infrastructure supporting high-volume Workflows and Conversations systems. Responsibilities include designing queueing pipelines, storage layers, caching, rate limiting, schedulers, and cloud infrastructure; optimizing databases, sharding, replication, and migrations; managing Kubernetes and GCP capacity; improving observability; debugging cross-layer incidents; and writing design documents and root-cause analyses.

Build and scale HighLevel’s Labs platform for feature flags, staged rollouts, experimentation, and customer feedback. Develop reliable backend services, APIs, frontend workflows, data models, caching, and distributed systems using modern technologies. Own complex features from design through production, contribute to architecture and technical decisions, implement observability and testing, support incident resolution, and collaborate with product, design, and engineering teams. The role also involves AI-assisted development, production support, code reviews, and mentoring.

Own the CRM Tasks product end to end by translating requirements into scalable frontend and backend systems, APIs, and workflows. Prototype, validate, ship, monitor, and improve production features independently while ensuring performance, reliability, and scalability. The role uses Vue.js, Node.js, and Go, with emphasis on full product ownership, rapid iteration, and sound engineering trade-offs.