Jobs at Wisdom AI

Lead customer-facing technical engagements to scope, deploy, and scale WisdomAI’s agentic intelligence solutions. Design enterprise context/semantic layers, solve data integration, governance, security, and performance challenges, build reusable context models and deployment frameworks, and translate customer needs into scalable product capabilities.

Provide Slack-first, white-glove technical support for enterprise customers: debug data connectivity (Snowflake/BigQuery), refine context models, assist GraphQL and Slack integrations, manage tickets in Pylon, run live consultations, document solutions, and report product feedback to engineering and product teams.

Build and evaluate LLM-based systems for code generation, document understanding, retrieval, and agentic pipelines. Design evaluation frameworks, work with customers and founders to shape product and roadmap, and influence engineering culture and tech stack.

Lead AI-native B2B product development by deeply understanding customer needs, defining clear problem statements, guiding technical execution, tracking qualitative and quantitative feedback, and aligning stakeholders to deliver features quickly and iteratively.

Build end-to-end user-facing surfaces for a generative UI platform using React/TypeScript/Node. Work on AI-generated visualizations, editable parameterized visuals, streaming chat-agent traces, and a React SDK. Collaborate with product, design, and customers across dashboard, chat, and integrations teams to ship polished, high-quality features.

Lead and scale end-to-end demand generation across events, paid media, ABM, webinars, and integrated campaigns. Own pipeline strategy, measurement, attribution, lead lifecycle, and HubSpot marketing automation. Partner with Sales, Product Marketing, and Design to turn programs into measurable, repeatable revenue growth.

Lead product marketing for an AI Data Analytics platform: develop positioning and messaging, run audience research, own product launches, competitive intelligence, sales enablement, content and pricing recommendations, and drive cross-functional alignment to accelerate adoption among analytics leaders, data teams, and business users.

Design and prototype enterprise UI/UX solutions for an AI analytics platform: define information architecture, run user research, create wireframes/mocks/prototypes, collaborate with engineering, and iterate from user feedback to improve data visualization and product experience.

Develop LLM-based systems for code generation, document understanding, and context synthesis. Build agentic pipelines and evaluation frameworks, collaborate with customers and founders to define product and engineering roadmap, and help shape engineering culture and tech stack.

Own the full enterprise sales cycle for AI-powered analytics: develop strategic account plans, qualify and close deals with Fortune 2000 clients, manage long-cycle procurement, drive co-sell motions with partners (Snowflake, Databricks, AWS/GCP), maintain CRM and accurate forecasting, and consistently exceed quota while positioning ROI of BI and cloud data solutions.

Build and own user-facing surfaces end-to-end for an AI-powered analytics platform. Implement generative UI, visualization and dashboard features, editable AI-generated visuals, streaming agent traces, and a React SDK. Collaborate closely with PMs, designers, and customers across frontend and backend work, prioritizing polish, performance, and trustworthy UX.

Build latency-critical, large-scale ML and data pipelines and cloud infrastructure for scalable, cost-efficient systems. Collaborate with customers and founders to define product and engineering roadmap and shape company engineering culture and tech stack.

Build and own deployments, observability, and scalable cloud infrastructure for ML and data pipelines. Collaborate with engineers, sales engineers, customers, and founders to define roadmap, tooling, and production change management.

Lead and grow the India engineering organization while remaining hands-on: participate in architecture and code reviews, mentor engineers, hire senior talent, and drive technical excellence across AI, data, and platform systems to build scalable, production analytics products.

Build and maintain scalable, low-latency data and ML pipelines on modern cloud infrastructure. Collaborate with founders and customers to define product and engineering roadmap, shape engineering culture, and ensure systems are cost-efficient, secure, and highly scalable.

Build and operate scalable, cost-efficient ML and data platform infrastructure. Own deployments and observability, improve production change management, work with cloud infra, collaborate with engineers, sales engineers, customers, and founders to define roadmap and scale onboarding.