Jobs at Weekday, Inc.

Develops new industrial paint business, manages key accounts, achieves sales targets, presents coating products, negotiates pricing and contracts, maintains CRM forecasts, resolves technical customer issues with application teams, supports order fulfillment, gathers product feedback, and manages collections and receivables.

Conduct daily field visits with surgeons, identify new customers and applications, coordinate medical-device designs with surgeons and design teams, promote company technology, develop hospital and surgeon partnerships, coordinate product dispatch, update Atulya software, follow up on payments, and escalate urgent customer issues.

Hands-on QC Engineer working on the shop floor to inspect incoming materials, in-process operations, and finished sheet-metal cookware. Develop inspection checklists, AQL sampling plans, SOPs, and QC reporting. Perform first-piece, in-process, and final inspections, conduct root-cause analysis, drive CAPA, maintain quality records, and improve processes to reduce rejection, rework, and scrap.

Develop, configure, customize, integrate, test, deploy, and support Guidewire PolicyCenter solutions in cloud environments. Build Guidewire components using Gosu, PCF, Rules Engine, and Data Model; develop REST API integrations; configure Property & Casualty insurance products and workflows; troubleshoot production issues; and collaborate with business and technical teams in an Agile environment.

Provides functional expertise in FMCG panel data, commercial analytics, and Revenue Growth Management. Analyzes market, sales, pricing, promotion, assortment, and trade investment data to identify revenue and margin opportunities. Uses Python and analytics techniques to prepare data, build models and dashboards, evaluate commercial effectiveness, and support scenario analysis. Partners with business, data engineering, data science, and technology teams while translating analytical findings into actionable recommendations for senior stakeholders.

Architect and build production-grade generative AI and agentic AI applications, including LLM workflows, multi-agent systems, RAG pipelines, APIs, and ML/GenAI infrastructure. Develop and optimize models, manage deployment and monitoring, apply responsible AI practices, and collaborate directly with customers. The role also involves mentoring engineers and shaping AI platform strategy.

Designs and develops complex cloud-based applications, software interfaces, and web services using Java and Vue3. Resolves critical issues across the software lifecycle, determines when new algorithms or models are needed, advises customers and management, and may lead teams on complex software tasks. AWS and Spring Boot experience are advantageous.

Designs and develops complex enterprise applications, software interfaces, web services, and cloud-based solutions using Java, Vue 3, AWS, and microservices. Resolves critical issues across the software lifecycle, advises on algorithms and models, and may lead teams while ensuring software specifications are achievable.

Architects and builds scalable generative and agentic AI products from prototype through production. Designs LLM workflows, prompts, multi-agent systems, RAG pipelines, and APIs using LangChain and LangGraph. Owns ML and GenAI pipelines, including training, deployment, monitoring, and lifecycle management. Works directly with customers and cross-functional teams, promotes responsible AI, mentors engineers, and shapes AI platform strategy.

Analyze syndicated market, consumer, and business data to identify trends, risks, opportunities, and actionable recommendations. Develop and maintain Power BI dashboards, reports, scorecards, KPI frameworks, and Excel-based analyses. Collaborate with stakeholders to define reporting requirements, validate data quality, and communicate insights to technical and senior business audiences. Support reporting frameworks, data models, and analytical processes while applying market research methodologies and business intelligence best practices.

Design, configure, and deliver SAP SD and LE solutions for S/4HANA implementations and enterprise transformations. Optimize order-to-cash processes, including sales orders, pricing, billing, shipping, transportation, and delivery. Lead requirements analysis, solution design, integrations with MM, FICO, and EWM/WM, testing, deployment, go-live, and post-production support while advising business stakeholders and technical teams.

Lead FMCG insights and analytics initiatives by analyzing consumer, market, category, sales, and performance data. Translate complex datasets into actionable recommendations, develop reports and dashboards, support commercial strategy, and present findings to senior stakeholders. Collaborate across Sales, Marketing, Finance, Supply Chain, and Leadership while improving analytics processes, managing multiple projects, and mentoring team members.

Lead global paid media strategy, budget allocation, campaign execution, audience development, attribution, experimentation, and performance optimization. Manage multi-channel campaigns across search, social, display, app, and affiliate channels while improving ROI, CAC, ROAS, LTV, and conversion. Partner with Data, Engineering, Product, Finance, Legal, and agencies; manage vendors and remote teams; report performance to leadership; and scale profitable customer acquisition and retention initiatives.

Evaluate datasets and AI-generated outputs for accuracy, relevance, consistency, and quality. Provide written feedback to improve AI system performance, follow project guidelines, support quality assurance, and communicate findings clearly. The role requires strong critical thinking, analytical reasoning, attention to detail, organization, and independent work in a remote environment. Prior AI experience is not required; data annotation, content evaluation, quality assurance, research, and AI project experience are preferred.

Own and scale an AI-powered product across frontend, backend, databases, infrastructure, and deployment. Build TypeScript, React, and Vite experiences; backend services; Vercel, Supabase, and PostgreSQL systems; AI-powered short-form content generation; internal workflow tools; and agentic integrations using MCP. Shape product and technical strategy, establish engineering standards, engage users, and eventually hire, mentor, and lead an engineering team.

Edit podcasts, events, social content, and showreels into polished short-form videos. Create motion graphics, animation, sound design, covers, thumbnails, and social posts. Direct AI-generated video and image assets using emerging creative tools, maintaining professional, on-brand quality. Help develop AI-native production tools and workflows while managing multiple projects, meeting deadlines, and communicating effectively in a fast-paced remote environment.

Own the architecture and delivery of production-grade generative and agentic AI systems, including LLM agents, RAG pipelines, multi-agent workflows, APIs, and cloud-native services. Establish AI engineering, evaluation, observability, guardrail, and LLMOps practices while mentoring AI/ML and backend engineers. Collaborate with Product, Data, Platform, Security, and Compliance teams to deliver scalable, secure, and business-ready solutions, and provide technical direction on GenAI strategy and architecture.

Evaluate and annotate physics content, create problem sets and technical documentation, and assess AI-generated responses for scientific accuracy. Contribute to dataset creation and provide expert feedback to improve AI model training. Collaborate remotely with project teams to ensure timely, high-quality deliverables and improve evaluation methodologies.

Contractor engineering SME to review and create technical engineering content for AI training: analyze documentation, develop examples and datasets, evaluate AI outputs for technical accuracy, and collaborate with teams to improve model performance and processes.

Evaluate and author high-quality computer science content to improve AI model reasoning and accuracy. Analyze complex CS problems, create scenarios/datasets, review AI outputs for correctness, and collaborate remotely to refine guidelines and documentation.