Top Tech Jobs & Startup Jobs

Leads a deeply technical Forward Deployed Engineering team delivering AI-powered customer solutions. Responsibilities include managing engineers, designing architectures, building and debugging production systems, leading enterprise deployments, integrating AI agents with business workflows, engaging customers, managing execution, and improving reliability and operational excellence.

Owns end-to-end B2B event marketing, including flagship events and executive roundtables. Partners with Sales and GTM to connect activations to pipeline goals, manages vendors and budgets, develops outreach and follow-up sequences, and measures qualified leads, influenced pipeline, and accelerated deals. Creates event briefs, playbooks, reports, and post-event content while coordinating with Brand and Video teams. The role is based in-office in Bengaluru and requires travel across India.

Design, build, deploy, integrate, and optimize production voice AI agents. Develop backend integrations with enterprise systems using APIs, WebSockets, webhooks, and CRM connections. Implement LLM orchestration, prompt design, guardrails, and tool calling. Monitor agent performance, analyze logs and traces, conduct root-cause investigations, and improve conversation funnels. Lead client workshops, collaborate with engineering teams, manage technical delivery, and support on-site deployment reviews.

Design, build, deploy, and support production-grade integrations between the Blue Machines platform and client systems. Develop API, cloud, and AI/LLM integrations; collaborate with clients on deployment, debugging, and optimization; and automate, document, and monitor workflows. The role requires Python or Java backend experience, cloud expertise, web technologies, authentication protocols, AI/LLM familiarity, and strong problem-solving and communication skills.

Design, build, deploy, integrate, support, and optimize production Voice AI agents. Develop backend integrations with enterprise systems using APIs, WebSockets, webhooks, and CRM connections. Implement LLM orchestration, monitor agent performance, analyze logs and traces, and perform root-cause analysis. Lead client workshops, manage technical delivery, and support live-call reviews and deployments.

Build and maintain scalable, low-latency backend systems for real-time AI and voice workflows. Responsibilities include developing microservices, APIs, streaming systems, concurrent and fault-tolerant code, observability, testing, deployment, and monitoring. The role integrates WebRTC and telephony protocols, Voice AI, LLMs, vector databases, and agent frameworks while collaborating with product, AI, and ML teams on multi-agent orchestration and automation.

Drive enterprise SaaS revenue through prospecting, relationship management, complex deal negotiation, and closing. Manage enterprise customers, build pipeline, develop sales strategies, and collaborate with legal, finance, marketing, product, technical, and operations teams. Help establish the company’s North American go-to-market sales motion for its conversational AI platform.

Owns quality for an AI agent platform across voice, web chat, WhatsApp, and email. Designs API, integration, regression, manual, exploratory, and production monitoring tests; integrates automation into CI/CD; investigates logs and traces; supports release sign-off; writes reproducible test documentation; and mentors the growing QA practice.

Drive enterprise sales for a conversational AI platform across Voice, Chat, SMS, and WhatsApp. Responsibilities include prospecting, relationship management, complex deal negotiation, closing and expanding large accounts, sales strategy, pipeline development, tailored presentations, and cross-functional collaboration. The role will also help establish Blue Machines’ North American go-to-market motion and sales processes.

Design, build, deploy, integrate, and optimize production voice AI agents for enterprise clients. Develop backend integrations using APIs, WebSockets, webhooks, CRM systems, cloud services, and AI frameworks. Monitor agent performance, analyze logs and traces, conduct root-cause investigations, optimize conversational funnels, and lead client workshops and deployment reviews.