Top Tech Jobs & Startup Jobs in Pune

Own the architecture and technical direction of HighLevel’s platform frontend, including the application shell, module federation, shared component library, build tooling, and performance standards. Lead migrations, independent release strategies, failure isolation, accessibility, internationalization, and observability. Remain hands-on with frontend architecture and code while mentoring engineers, driving cross-team adoption, and optimizing large-scale web applications.

Lead architecture and delivery of scalable, multi-tenant industry solutions and platform capabilities. Design configurable workflows, integrations, event-driven systems, feature rollouts, observability, and data isolation. Partner with product, design, and go-to-market teams to validate solutions and measure customer impact. Mentor engineers, provide technical direction, and ensure quality, performance, security, and reliability across production systems.

Lead the design and production deployment of LLM-powered AI agents, generative AI systems, and retrieval-augmented generation infrastructure. Build and fine-tune models, develop multi-step agents, apply data science methods, and establish evaluation, monitoring, observability, and feedback systems. Partner with product, backend, and infrastructure teams to scale AI capabilities across messaging, scheduling, sales, and operations while influencing the AI roadmap and mentoring engineers.

Lead the Platform Services engineering team responsible for shared infrastructure, internal tooling, and core services. Own distributed systems architecture, cloud reliability, observability, cost optimization, roadmap delivery, and incident management while remaining hands-on with code and production systems. Hire, mentor, and develop engineers; establish technical standards; and collaborate with product engineering, SRE, security, and leadership. Drive AI-assisted engineering practices and platform automation.

Build and lead HighLevel’s customer growth and activation function for an installed SMB and agency customer base. Own lifecycle journeys, trial-to-implementation conversion, activation, expansion revenue, AI deflection quality, customer scorecards, enablement, experimentation, and cross-functional execution. Establish measurable outreach plays with holdout groups, define customer cohorts, improve first-90-day engagement, and manage a team assembled to deliver a new lifecycle motion.

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.