Jobs at Wisdom AI

Provide real-time technical support to enterprise customers through Slack and Pylon. Troubleshoot data connectivity, SQL queries, schemas, APIs, integrations, permissions, AI context models, and platform configurations. Manage support cases through resolution, conduct customer consultations, document solutions, and communicate recurring issues to Product and Engineering. Help customers configure metrics, evaluations, workspaces, permissions, and row-level access controls.

Provide real-time technical support to enterprise customers through Slack and Pylon. Troubleshoot data connectivity, SQL queries, schemas, APIs, GraphQL integrations, AI configurations, permissions, and data models. Manage support cases through resolution, conduct customer consultations, document solutions, and relay product feedback to engineering and product teams.

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.

Build LLM-powered code-generation, document-understanding, context-synthesis, and agentic workflows. Develop evaluation frameworks for query processing, collaborate with customers and founders on product and engineering direction, and help shape the company’s engineering culture and technology stack. The role requires strong analytical skills and experience solving difficult NLP problems, with search, retrieval, LLM, and evaluation pipeline experience preferred.

Build and scale cloud infrastructure supporting ML and data pipelines. Own platform deployments, observability, production change management, and highly available systems. Collaborate with software engineers, sales engineers, customers, and founders to improve onboarding, define product and engineering roadmaps, control infrastructure costs, and shape the company’s engineering culture and technology stack.

Build scalable, secure backend infrastructure and large-scale data pipelines for latency-critical analytical workloads. Design cost-efficient cloud systems, collaborate with customers and founders on product and engineering priorities, and help shape the company’s engineering culture and technology stack.

Own technical positioning, messaging, launches, demos, content, competitive intelligence, and sales enablement for an agentic analytics platform. Translate data engineering, semantic modeling, AI, governance, and analytics workflows into credible narratives for technical and executive audiences. Conduct customer and competitive research, build GTM assets, support technical evaluations, and partner cross-functionally with Product, Engineering, Sales, Solutions Engineering, Customer Success, and Marketing.

Lead partnership and marketplace strategy, negotiate and structure complex alliances, drive post-signature GTM and co-selling motions, own marketplace listings and revenue growth, coordinate cross-functional enablement, and partner with Product and Engineering to prioritize integrations.

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.

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.

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.

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.

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.

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.

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.

Design and run experiments to improve NL-to-SQL, retrieval, ranking, conversational understanding, and agentic reasoning. Build evaluation frameworks, prototype and productionize LLM techniques (fine-tuning, distillation, retrieval), and translate research into production systems for enterprise customers.

Execute call-first outbound prospecting to generate qualified pipeline, partnering with AEs on territory strategy. Use AI tools to research and personalize outreach, document activity in HubSpot, and meet activity, meeting, and pipeline targets while participating in coaching and continuous development.