Jobs at BJAK

Build and maintain production Android applications with AI-native interactions. Integrate chat, vision, voice, and recommendation features through backend APIs; design resilient streaming and partial-result experiences; optimize performance, memory, and responsiveness; and implement analytics, logging, monitoring, security, and feedback systems. Collaborate with backend and ML engineers on API contracts, diagnose production issues, and deliver stable, scalable mobile experiences.

Build and maintain production-grade iOS applications using Swift and SwiftUI, integrating AI features through backend APIs. Design reliable AI interaction patterns, optimize performance, memory, battery, and latency, and support on-device inference. Collaborate with backend and ML engineers on APIs and system behavior, capture user feedback for AI evaluation, maintain App Store quality, and diagnose production issues through monitoring and root-cause analysis.

Define the AI-native phone’s hardware platform strategy, roadmap, and specifications. Evaluate mobile SoCs and components, including CPU, GPU, NPU, memory, connectivity, power, thermal, and battery capabilities. Translate product and AI requirements into hardware decisions, assess platform customization needs, collaborate with ODMs, OEMs, and chipset vendors, review architecture proposals, and establish validation criteria for current and future on-device AI workloads.

Evaluate, benchmark, deploy, and optimize AI models for on-device execution on Android hardware. Responsibilities include integrating models into applications and system services, reducing latency, memory use, and power consumption, applying quantization and compression, leveraging CPU, GPU, and NPU acceleration, and building hybrid local/cloud inference routing with agent systems.

Define the product vision and user experience for an AI-native phone. Identify high-value workflows, design proactive interactions across the operating system and applications, translate concepts into engineering requirements, prioritize prototype and launch capabilities, evaluate technical feasibility with Android and AI teams, and validate interaction patterns through user research.

Integrate AOSP or custom ROMs with smartphone hardware, including BSPs, vendor HALs, firmware, drivers, boot processes, cameras, sensors, modems, Wi-Fi, and Bluetooth. Troubleshoot hardware and firmware compatibility, collaborate with OEMs, ODMs, and chipset vendors, and optimize device power consumption and performance.

Build agent capabilities for AI phones, including workflow orchestration, tool integrations, context retrieval, memory, multi-step execution, long-running stateful workflows, and reliability improvements. Integrate local and cloud model providers, develop evaluation and regression tests, and support production AI infrastructure. The role requires backend or AI application engineering expertise, programming proficiency, LLM API and tool-calling experience, and knowledge of APIs, distributed systems, state management, and asynchronous execution.

Build integrations between AI agents and first-party applications, exposing structured actions and information retrieval interfaces. Develop cross-application workflows, reusable SDKs, and reliable asynchronous APIs supporting search, creation, updates, sending, and deletion. Manage authentication, authorization, and permissions; investigate integration limitations; and collaborate with Android engineers on system-level application access.

Develop and modify Android system services, privileged APIs, and AI integration interfaces at the OS level. Build reliable agent-to-system execution capabilities, manage permissions, IPC, application lifecycle, and background execution, and optimize system performance and resource consumption. Collaborate with AI agent engineers while debugging and improving Android platform functionality.

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.

Design and deliver pixel‑perfect mobile interfaces for iOS and Android across financial products. Create wireframes, flows, prototypes and production-ready UI, build and maintain design systems, collaborate with engineers, and iterate based on analytics and user feedback to ensure usability, accessibility and platform consistency.

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.