Jobs at ODAIA Intelligence Inc.

Owns new business growth and strategic account expansion across mid-market and enterprise pharmaceutical organizations. Leads consultative discovery, enterprise sales cycles, solution positioning, proposals, negotiations, and closing. Builds executive relationships, manages complex buying groups, develops value-driven proposals with cross-functional teams, and supports onboarding and client success. Maintains pipeline accuracy, forecasting, CRM discipline, and account expansion while translating AI-powered analytics into measurable commercial outcomes.

Owns enterprise sales and revenue growth across Life Sciences accounts, leading complex SaaS and analytics sales cycles from prospecting through expansion. Builds executive relationships, develops ROI-focused business cases, manages pipelines in Salesforce, and collaborates with cross-functional teams on proposals, demonstrations, onboarding, and account strategy. The role also provides market intelligence and customer feedback to influence product development and positioning.

Leads ODAIA’s strategic commercial accounts and GTM transformation for life sciences clients. Advises C-suite pharma executives, develops account and segment strategies, translates business challenges into outcome-driven solutions, drives strategic wins and account expansion, and oversees post-sale value realization. Leads cross-functional specialist pods, influences product and engineering priorities, and helps scale ODAIA’s consultative, AI-powered commercial effectiveness model.

Implements and configures an AI platform by integrating customer data, building ETL workflows, troubleshooting pipelines, managing recurring data deliveries, and automating manual processes. The role collaborates with customers and internal teams to define technical requirements, resolve implementation issues, deploy tailored solutions, and maintain data security and privacy.

Build and operate full-stack product capabilities using React, TypeScript, backend services, APIs, cloud infrastructure, and data systems. Responsibilities include implementation, testing, deployment, monitoring, incident learning, and technical design. The role partners with product, design, and ML teams to turn life sciences data and AI capabilities into accessible customer experiences, while using coding AI agents and modern delivery practices.

Own complex customer data implementations from technical discovery through production go-live. Build automated ETL workflows, scalable data ingestion solutions, validation frameworks, and data-quality processes using Python, SQL, PySpark, Snowflake, and AWS. Troubleshoot integrations and production issues, ensure compliance with security and privacy requirements, mentor junior engineers, and improve implementation standards and tooling while working directly with technical and non-technical customer stakeholders.

Own full-stack product capabilities from problem framing through deployment and iteration. Build React and TypeScript user experiences, AWS Lambda computation services, scalable APIs, and backend systems across AWS, Kubernetes, Snowflake, PostgreSQL, DuckDB, and DataFusion. Lead technical design, code reviews, architecture discussions, testing, observability, and mentoring while partnering with product, design, ML engineering, and leadership on roadmap decisions.