The Role We’re looking for a highly technical, hands-on Staff Software Engineer to lead the architecture, development, and scalability of platforms powering our operations, AI data workflows, and intelligence systems. You’ll serve as a technical lead across critical engineering initiatives, building the infrastructure that supports complex data pipelines, expert onboarding, workflow orchestration, and the delivery of actionable insights. This role requires deep engineering expertise, strong architectural judgment, and the ability to drive technical execution across multiple systems. You'll work closely with engineering teams to build reliable, high-performance platforms while incorporating AI agents, intelligent automation, and modern software engineering practices into how we design, build, and operate software. What You’ll Be Doing Lead Platform Architecture: Drive the technical design, development, and scalability of platforms supporting operational workflows, data pipelines, expert lifecycle management, and intelligence delivery. Build Scalable Backend Systems: Design distributed services, APIs, event-driven architectures, and integrations that support complex workflows, high-volume data processing, and cross-platform communication. Develop AI Data Infrastructure: Build systems supporting expert-generated data, enterprise AI datasets, human feedback, and multimodal data workflows used in AI model training and evaluation. Drive Workflow Orchestration: Architect solutions for pipeline creation, talent onboarding, subscription management, task execution, and automated operational processes. Enable Data Intelligence: Develop services that aggregate, process, and surface data, metrics, and insights from multiple systems into unified, actionable experiences. Establish Agentic Engineering Foundations: Design reusable infrastructure for AI agents, including tool calling, orchestration, context management, structured outputs, evaluation, observability, and reliable execution. Stay Hands-On: Write production-grade code, lead technical design reviews, troubleshoot complex issues, and establish engineering standards across critical systems. Improve Engineering Productivity: Leverage AI-assisted development, automated testing, CI/CD, and developer tooling to accelerate delivery and improve software quality. Provide Technical Leadership: Mentor engineers, guide architectural decisions, reduce technical debt, and collaborate with Product, AI/ML, Data, and Operations to deliver scalable solutions. What We’re Looking For 10+ years of software engineering experience, with a strong track record of designing, building, and scaling complex production systems. Deep hands-on programming expertise in Python, TypeScript, or similar modern languages, with strong backend engineering fundamentals. Extensive experience with distributed systems, microservices, APIs, event-driven architectures, asynchronous processing, and workflow orchestration. Strong system design and architecture skills, including the ability to make technical trade-offs across scalability, reliability, performance, and maintainability. Experience building data-intensive platforms, including data ingestion, processing pipelines, ETL/ELT workflows, and analytics infrastructure. Practical experience with LLMs and agentic systems, including tool calling, agent orchestration, RAG, context management, and evaluation frameworks. Experience with cloud infrastructure such as AWS, GCP, or Azure, containerization, Kubernetes, databases, and CI/CD pipelines. Strong understanding of engineering quality, including automated testing, observability, performance optimization, and production reliability. Proven technical leadership, with experience guiding engineers, driving cross-team initiatives, and owning complex technical projects from design through production. High ownership and execution mindset, with the ability to navigate ambiguity, solve difficult technical problems, and deliver in fast-paced environments. Preferred Qualifications Experience in AI research labs, AI-native companies, or high-growth technology startups. Experience with human data infrastructure, including expert-generated datasets, data annotation, human-in-the-loop workflows, preference data, and model evaluation pipelines. Familiarity with foundation model training and evaluation workflows, including multimodal datasets, robotics data, and human demonstrations. Experience building enterprise AI data platforms, retrieval systems, or infrastructure supporting AI agents. Hands-on experience with agentic frameworks and orchestration tools such as LangGraph, Temporal, MCP, or similar technologies. Experience designing real-time analytics, operational intelligence, and data aggregation systems across multiple platforms. Familiarity with AI-assisted development tools, agent-driven engineering workflows, and modern developer productivity practices.

About Quickhyre AI

QuickHyre AI is an online job portal and HRMS software platform for hiring and workforce management, trusted by over 10 million active users. It connects freshers and experienced professionals across all career levels with verified job opportunities, while enabling companies to hire, onboard, and manage employees through a single system. Candidates use QuickHyre AI to search and apply for jobs across entry-level, mid-level, and senior roles, including internships and contract positions across tech and non-tech domains. Employers use QuickHyre AI as a hiring platform, applicant tracking system (ATS), and HRMS to post jobs, screen candidates, manage applications, onboard hires, and maintain employee records. Built for startups, growing companies, and enterprises, QuickHyre AI reduces irrelevant applications, improves hiring efficiency, and simplifies HR operations. By combining job discovery, online recruitment, and HR management software, QuickHyre AI supports end-to-end talent acquisition and workforce administration at scale.