Top Tech Jobs & Startup Jobs

Design and implement scalable backend systems and AI-driven workflows, optimize for performance and availability, integrate cloud services and databases, collaborate with product and customers, write maintainable code, and mentor junior engineers.

Lead architecture, implementation, and optimization of scalable backend systems and AI-driven workflows. Integrate LLMs, agentic frameworks, and automation to enhance sales intelligence. Drive features from design through deployment, ensure high availability and low latency, write maintainable code, and champion engineering best practices.

Own and scale large data ingestion and enrichment pipelines using SQL and Python. Build AI-powered systems with LLMs, embeddings, and vector search for extraction, classification, and entity resolution. Design data models, maintain warehouse/CRM sync, ensure data quality, and optimize AI infrastructure for cost and performance while mentoring teammates.

Own and prioritize the data platform roadmap (ingestion, enrichment, matching, vertical models, warehouse/CRM sync). Turn ambiguous data problems into buildable specs, manage data quality feedback loops, evaluate third-party data vendors, control enrichment/AI costs, and partner with engineering, design, and GTM to ship high-impact data features.

Own end-to-end finance for the India entity including budgeting, forecasting, expense and invoice management, and audit-ready reporting. Build and document scalable processes, manage vendors and operational execution, keep financial and operational data clean, and lead cross-functional finance and ops projects from scope to delivery. Partner with leadership on reporting, compliance, and process improvements.

Build and improve backend systems and AI-driven workflows, integrate AI models and low-code tools, optimize a scalable, low-latency platform, write well-tested code, collaborate with founders, product, and customers, participate in code reviews, and contribute to engineering culture.

Serve as a consultative post-sale partner to enterprise customers, diagnose funnel performance issues (data, targeting, execution), advise on dialer, email, cadence, copy, and tracking, drive account expansion, align with Professional Services and post-sales leadership, and establish funnel benchmarks by segment to pinpoint pipeline breakdowns.