Top Tech Jobs & Startup Jobs

Build and optimize multilingual ASR/TTS and voice-to-voice systems for conversational AI agents. Develop agentic RAG pipelines, LLM orchestration, self-learning agents, and guardrails supporting interruptions and natural pauses. Deploy scalable, secure, reliable ML systems in low-latency real-time environments while collaborating with product, engineering, and MLOps teams.

Architect and lead scalable infrastructure for low-latency voice and chat AI agents. Design multi-cloud distributed systems, real-time inference pipelines, and resilient production platforms. Establish reliability, observability, performance, security, and compliance practices while optimizing GPU and TPU utilization. Translate AI research into production deployments, evaluate inference technologies, mentor engineers, and guide enterprise-grade architecture across Kubernetes, MLOps, model serving, and microservices.

Research and write concise scripts for solo and guest podcast episodes, conduct in-depth guest and subject research, support outreach and coordination, and help shape editorial strategy. The role requires translating complex technical and interdisciplinary ideas into engaging narratives for broad audiences while aligning with the founder’s vision.

Partners with leadership to define and execute strategic initiatives, improve business operations, analyze performance, and develop actionable recommendations. Owns planning, OKRs, reporting, dashboards, and process improvements while leading cross-functional projects from problem framing through implementation. Advises founders on business-critical decisions, market opportunities, and growth levers in a fast-paced, in-office startup environment.

Own the production systems behind autonomous enterprise AI agents, including memory, orchestration, scheduling, model steering, latency, deployment, operator tooling, debugging, and benchmarking. Build reliable distributed or stateful systems using Python, shell, and TypeScript/Node.js. Apply strong engineering judgment to security, multi-tenant deployments, testing, observability, and AI agent limitations in a fast-moving startup.

Build and deploy production-grade AI tutoring workflows, including agentic tutoring, grading, retrieval and grounding, personalization, and multimodal pipelines. Optimize latency and cost, implement evaluations, observability, reliability, and safety controls, and own features from product requirements through deployment and iteration. Collaborate with product, design, and education teams to translate learning goals into effective AI behavior.

Own the production engineering of autonomous AI agents, including memory, orchestration, scheduling reliability, tool capabilities, latency optimization, deployment, debugging, benchmarking, and operator tooling. Build trustworthy LLM applications beyond demos using strong testing, evidence-based decisions, deterministic system design, and production ownership of distributed or stateful systems. The role also involves supporting multi-tenant deployments, security, and rapid startup product development.

Own DreamBook’s product vision and 0-to-1 global launch, spanning AI-assisted long-form writing workflows, UX, publishing compliance, digital distribution, print-on-demand integration, and team building. Partner with founders and engineering leadership while defining strategy, user journeys, AI capabilities, go-to-market scaling, and product culture.

Build and own Proofline’s interactive real-time graph canvas, enabling collaborative knowledge mapping across tens to thousands of nodes. Responsibilities include designing direct-manipulation interactions, optimizing rendering performance through virtualization and semantic collapse, implementing WebSocket/CRDT collaboration, contributing across the full stack, and maintaining a minimal design system. The role requires strong product judgment, production engineering discipline, and comfort working onsite in a fast-moving founding team.

Own Proofline’s Python microservices backend platform, production reliability, deployment, observability, monetization systems, enterprise readiness, and tier strategy. Lead and mentor a four-engineer Bengaluru team, establish engineering standards, review backend and AI-generated code, manage roadmap delivery with the founder, and support hiring. The role requires strong cloud, billing, multi-tenancy, AI-assisted development, and zero-to-one product engineering experience.