IntroductionADPCX is a challenger technology company building the next generation of AI-powered customer experience.Backed by a group managing 27,000+ clients, we have been developing AI technology for years, combining deep operational experience with engineering, data and real-world deployment at scale.We are building across Voice AI, conversational AI, autonomous agents, agent assist, intelligent automation and real-time analytics, designed to transform how businesses interact with their customers.We move fast, challenge established thinking and build technology to disrupt a global industry.We are looking for ambitious engineers and AI talent who want to build, challenge and own, not simply execute.If you want to help build technology capable of changing an industry, ADPCX is where you can make an impact.

About the roleYou'll design and own backend systems across our product suite — AI platforms, real-time services, and data-heavy applications. We're looking for an architect-minded engineer who can take a high-level idea and turn it into a system that holds up at scale. You should be comfortable in the AI space; deep voice experience is a strong plus.

What you'll do

Own backend architecture end to end — from design doc to production serviceBuild event-driven, distributed systems that scale with traffic and stay debuggableTranslate ambiguous product ideas into concrete system designs,



then ship themMake deliberate trade-offs on latency, throughput, cost, and failure behaviourSet engineering standards: code review, testing, observability, documentationWork alongside AI, infra, and product teams to move features from prototype to productionMust-have

5+ years backend engineering, strong in PythonProven system design ability: distributed systems, queuing, caching, data modelling, API designHands-on experience with event-driven architecture — message brokers, streaming, async workflows (Kafka, RabbitMQ, Redis Streams, or similar)Experience scaling production systems under real load, with real failure modesWorking familiarity with LLMs and the current AI tooling landscapeStructured engineering habits — clean code, explicit interfaces, disciplined version control and reviewsAbility to own a problem end to end with minimal directionStrong plus

Experience architecting voice systems: voice bots, real-time speech pipelines, STT/TTS integrationScaling AI products in production — inference serving, latency tuning, cost per requestRAG pipelines and vector databasesTelephony exposure (SIP, Asterisk, FreeSWITCH, WebRTC)Kubernetes, Docker, CI/CD, cloud infrastructureWhat we look forSomeone who thinks in systems, not tickets. Who asks what happens at 10x load before writing the first line. Who cares what the code looks like six months from now.

📌 Sr. Backend Engineer: (Mumbai)
🏢 CC33 Global
📍 Mumbai