• Lead the design and development of infrastructure, automation frameworks, and internal engineering tools. • Build scalable services, APIs, dashboards, workflow engines, and integrations that improve developer efficiency and operational visibility. • Develop LLM-based workflows for triage, summarization, code and log analysis, test workflow assistance, report generation, and knowledge retrieval. • Integrate tooling with CI/CD systems, source control, issue tracking, test infrastructure, dashboards, and internal engineering services. • Define architecture, coding standards, evaluation methods, and reliability practices for automation and LLM-enabled systems. • Mentor engineers, review designs, and provide technical leadership across infrastructure and tooling projects.

Role Description We are seeking a seasoned, battle-tested QA Lead & AI Brand Evaluation Strategist to take full ownership of the quality, integrity, and strategic evaluation of our rapidly expanding suite of agentic and AI-powered product features. This is not a traditional, checklist-driven QA role. You will operate in a highly dynamic, non-deterministic environment, leading the strategy to evaluate probabilistic software at scale. Your core mission is to transform complex, ambiguous business requirements into robust evaluation criteria and scoring systems. You will lead the design of tools and frameworks that process massive volumes of data, ensuring our brand scoring metrics are precise, reliable, and actionable. What you'll do - Strategic QA Leadership: Own the end-to-end testing and evaluation strategy for multi-agent architectures and high-volume data pipelines, defining direction even when product requirements are fluid or ambiguous. - Business-to-Evaluation Translation: Act as the primary bridge between Product, Data Science, and Engineering. Translate complex business objectives into concrete, data-driven evaluation criteria and operational rubrics. - Brand Scoring Architecture: Oversee the methodology for scoring brands against complex criteria, ensuring that automated systems accurately transform massive datasets into precise, reliable business metrics (e.g., Share of Model, Net Sentiment). - Framework & Tool Building: Drive the creation of internal tools, data-driven testing pipelines, and validation frameworks capable of handling non-deterministic AI outputs and large-scale information ingestion. - System Integrity & Governance: Establish risk-adaptive guardrails and checkpoints to ensure data precision, compliance (PII), and logical reasoning across complex, multi-step agentic workflows. - Lead & Orchestrate Evaluation Frameworks: Define, architect, and oversee validation processes for application layers, complex API workflows, and the data transformation engine. - Define Brand Scoring Criteria: Establish the mathematical and logical rules that operate over massive data volumes to audit whether brand evaluations match underlying raw metrics reliably. - Direct "Golden" Test Set Curation: Lead the strategy for compiling, synthesizing, and maintaining massive baseline validation datasets to test edge cases, user intent, and model drift. - Drive Adversarial & Ambiguity Testing: Design "red-teaming" scenarios and boundary testing to evaluate how gracefully the system handles prompt variations, conversational drift, and highly ambiguous data inputs. - Tooling Innovation: Collaborate with engineering to build proprietary testing tools or automation scripts that streamline the ingestion and analysis of high-volume data for QA purposes. - Defect Profiling & Root-Cause Strategy: Move beyond simple bug logging; analyze trends in statistical behavioral defects and guide cross-functional teams toward systemic root-cause resolution. - Platform Observability & Metrics: Monitor cloud logging and data observability dashboards to track execution latency, data drift, and accuracy trends, transforming insights into platform optimizations. Qualifications - 8+ years of proven experience in QA Engineering, Systems Analysis, or Software Testing, with at least 2+ years in a Lead or Strategic role managing complex, data-heavy digital platforms. - Proven "cancha" (battle-tested experience) leading QA initiatives in fast-paced environments where requirements are not fully defined, showing a high capacity to resolve ambiguity and establish order. - Strong data-driven background. Exceptional capability to shift away from purely binary (pass/fail) testing toward evaluating data trends, composite scoring, and statistical outcomes. - Comfortable working with big data contexts—understanding how information flows from raw ingestion (data lakes) through transformation layers to user-facing dashboards. - Deep expertise in traditional and modern software testing methodologies, Agile environments, risk management, and project tracking ecosystems (such as JIRA). - Practical experience with Python, JavaScript, or SQL to query databases, manipulate data structures, and trigger/build automated evaluation pipelines. - Deep operational awareness of LLM behaviors, agentic workflows, and typical AI challenges (hallucinations, context limits, instruction adherence). Preferred Skills and Qualifications - Experience with LLM evaluation frameworks (e.g., Ragas, LangSmith, TruLens) or prompt engineering playgrounds. - Familiarity with cloud data warehouses and analytics platforms (e.g., BigQuery, Databricks, Google Cloud Platform components). - Experience building internal scripts or lightweight tools specifically designed to automate QA data validation.

• Build a Universal Provisioning Engine and custom integration layers that satisfy external auditors while keeping internal teams focused on shipping features. • Eliminate the engineering "interruption tax," provide leadership with a real-time, data-driven view of our risk posture, and ensure continuous compliance with zero audit surprises. • Engineer a centralized security telemetry system that programmatically captures control evidence and health in real-time, transitioning from manual snapshots to continuous data streams for an 'always-on' view of our security posture. • Architect solutions for systems that lack native IGA support. • Partner with our risk management function to build a secure mechanism to generate agentic risk assessments workflows using the data and results from what is collected.

Role Description We are looking for detail-oriented QA Clipper Interns who can watch long-form videos and create high-quality clips based on clearly defined rubrics and training provided by our team. This is a fully remote internship with daily payouts, performance incentives, and clear milestones. If you enjoy watching videos, have good attention to detail, and want to earn from home—this role is for you. Key Responsibilities - Watch long-form videos at 4x speed - Create accurate clips strictly based on QA rubrics & training - Ensure clips meet quality, timing, and relevance standards - Maintain daily productivity targets - Follow feedback and improve clipping accuracy over time Daily Target - 30 hours of video clipping per day (Achievable by watching content at 4x speed) Internship Stipend - ₹24,000 / month + bonus Job Type - Internship | Remote | Flexible Hours Our Values - Empathy, Trust & Candor: We put ourselves in the shoes of our colleagues and customers and don’t shy away from uncomfortable conversations, instead building trust through honest and direct feedback. - Bias for Action: We practice high-velocity decision-making, clear-eyed that we often operate with incomplete information. Growing quickly means it’s OK to be wrong, so long as we learn from our mistakes and course correct! - Always Be Learning: We’re a curious bunch, and with AI transforming our workplace we encourage everyone to learn from each other, compounding our knowledge and experience to help us change an entire industry. - Act Like an Owner: We work long, hard, and smart, building products that delight our users and drive growth. Your ability to impact Instawork is limited only by your courage and conviction, not your job description. Company Description Founded in 2015, Instawork is the nation’s leading online labor marketplace for food services, hospitality, light industry, and logistics, connecting more than 7M skilled workers with local restaurants, hotels, warehouses, stadiums, and more. Our AI-powered platform serves thousands of businesses across more than 50 major markets in the United States and Canada. We're not just helping fill shifts, we're supporting local economies—and we're just getting started! - Instawork has been featured by CBS News, The Wall Street Journal, The Washington Post, and the Associated Press. - Forbes included us on their Next Billion Dollar Startups list. - RetailTech Breakthrough named us Workforce Hiring Solution of the Year for 2025. - Inc. 5000 recognized us as one of the country's top 10% fastest-growing companies two years in a row. Join our team to help us build something that matters! We’re looking for superstars who want to help us shape the future of work. With hubs in San Francisco, Bangalore, and Chicago, city offices in New York, Phoenix, and Singapore, we're back to working together in-person five days a week because we believe the best ideas happen when great people collaborate face-to-face. We also value diverse perspectives and encourage applications from candidates of all backgrounds. Ready to make an impact? Learn more at www.instawork.com/about .