Top Tech Jobs & Startup Jobs in Chennai

Lead Android platform architecture and AOSP-based custom ROM development for an AI-native phone. Define OS-level AI integration, system services, privileged APIs, permissions, security architecture, and platform extensions. Partner with hardware vendors and ODMs on device integration, assess technical trade-offs, and establish engineering standards. The role requires deep Android internals expertise, platform-level feature delivery, ROM modification experience, and strong Java, Kotlin, and C++ skills.

Develop and modify Android Framework components, system services, privileged APIs, and secure AI-agent integrations. Work on application lifecycle, permissions, background execution, first-party app integration, OS stability, and performance while collaborating with agent engineers. Requires strong Android, Java or Kotlin, AOSP, Binder IPC, permissions, and complex debugging experience.

Design AI-native experiences for everyday phone use, including proactive interactions, voice, touch, conversational interfaces, contextual workflows, and transparent agent actions. The role involves prototyping and validating new interaction models while collaborating closely with product and engineering teams. Candidates should have strong product and interaction design experience, mobile or complex workflow design expertise, prototyping skills, usability knowledge, and strong product thinking.

Plan, manage, and optimize paid user acquisition campaigns across multiple advertising platforms. Own budgets, analyze CAC, ROAS, LTV, cohorts, attribution, and payback periods. Run experiments across audiences, bids, landing pages, and creatives; collaborate with creative teams; and scale profitable campaigns across markets using data-driven acquisition strategies.

Lead product strategy and execution for an AI-native mobile communication application. Define requirements, user journeys, priorities, acceptance criteria, and roadmap; collaborate with design and engineering through launch and iteration. Analyze usage, feedback, and performance metrics to improve activation, engagement, and retention. Research user behavior, competitors, and market trends to identify opportunities and guide product decisions.

Leads product strategy, roadmap, prioritization, technical scope, and launch planning for an AI-native communication application. Partners with engineering, design, and business stakeholders on architecture, scalability, reliability, and product trade-offs. Defines success metrics and uses adoption, engagement, retention, and user feedback to guide investments. Requires extensive technical product management experience and a track record of launching and scaling complex products.

Define product roadmaps, requirements, and success metrics for AI-native communication applications. Translate user needs into technical features and workflows, evaluate architecture and engineering trade-offs, and lead products from planning through launch and iteration. Analyze user behavior, experiments, and performance to improve adoption, engagement, retention, and business outcomes. Assess market opportunities and collaborate with engineering on complex systems, integrations, reliability, and performance.

Integrate security into software delivery and infrastructure workflows across AWS and GCP. Build scanning into CI/CD pipelines, maintain security guardrails, secure containerized workloads, implement least-privilege access and secrets management, and support compliance with SC TRM and BNM RMiT. Improve monitoring, vulnerability reporting, incident readiness, and secure delivery practices while collaborating with platform and engineering teams using multiple programming languages.

Owns the end-to-end product direction and quality of AI-powered systems, translating model capabilities, evaluations, and engineering constraints into requirements and priorities. Partners closely with ML, backend, and client engineers on system design, experimentation, evaluation frameworks, reliability, safety, latency, cost, and user experience. Identifies failure modes, establishes quality standards, drives rapid iteration, and ensures AI features are useful, predictable, understandable, and trusted.

Own technical direction and hands-on execution for major products, systems, and engineering initiatives. Design scalable systems across backend, frontend, APIs, databases, and infrastructure; write and review code; lead architecture decisions; solve production issues; convert ambiguous problems into technical plans; improve engineering quality; and mentor engineers across teams.