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Participate in Veeva’s Consultant Development Program, configuring cloud software, testing features, solving customer problems, managing deliverables, and advising Life Sciences customers. The role includes intensive onboarding, direct customer collaboration, and progression to Consultant in under two years. Candidates should be recent bachelor’s or master’s graduates with strong communication, analytical ability, curiosity, initiative, and willingness to travel up to 20–30%.

Build and ship AI features, including RAG pipelines, agentic workflows, and LLM applications on AWS. Develop asynchronous Python backend services and React/TypeScript frontend features, while owning testing, CI, deployment, and observability. Work across backend, frontend, cloud, and applied AI in a remote team, integrating with Veeva Vault and CRM APIs.

Build and deploy AI-powered features, including RAG pipelines, agentic workflows, and LLM applications on AWS. Develop async Python backend services and React/TypeScript frontend features, manage testing, CI, observability, and cloud deployment, and integrate Veeva platform APIs. The role offers end-to-end ownership in a fully remote, fast-moving team while spanning backend, frontend, cloud infrastructure, and applied AI engineering.

Business Consulting Intern supporting project teams on client workshops, requirements gathering, data sourcing and analysis, insight development, and presentation creation. The role provides exposure to consulting methodologies, life sciences business processes, and data-driven problem solving. Interns own project assignments, process data, communicate findings, and present recommendations to consulting teams and clients.

Pre-sales Solution Consultant responsible for demonstrating Veeva Vault CRM and AI solutions to life sciences customers. The role includes consultative discovery, solution design, product demonstrations, RFX responses, technical deal strategy, workshops, implementation handoffs, customer relationship development, marketing support, and product feedback. Candidates must have relevant pre-sales, implementation, consulting, or pharmaceutical sales experience and be willing to travel up to 30%.

Own the end-to-end product lifecycle, including strategy, roadmap, market research, requirements, user stories, AI feature integration, and post-launch optimization. Lead cross-functional collaboration among stakeholders, design, engineering, and QA teams. Define KPIs, use analytics to guide iterations, establish acceptance criteria, and ensure product stability and performance across SaaS and cloud applications.

Drive strategic growth across enterprise Consumer Goods and Food & Beverage accounts by identifying targets, executing outbound and inbound lead strategies, building executive relationships, generating pipeline, and leading selected enterprise sales cycles. Maintain accurate CRM reporting and collaborate with Solution Consulting, Marketing, and Strategy teams to position Veeva Quality Cloud and deliver quality transformation outcomes.

Drive strategic growth across enterprise Consumer Goods and Food & Beverage accounts by creating pipeline, conducting targeted outreach, qualifying inbound leads, building executive relationships, and leading selected enterprise sales cycles. The role advises senior leaders on quality transformation, expands customer relationships, maintains accurate CRM reporting, and collaborates with solution consulting, marketing, and strategy teams. Candidates need SaaS sales or account management experience, C-level engagement skills, strong communication, strategic execution, and English fluency.

Lead go-to-market, partner adoption, and commercial success for Crossix Analytics partner products. Build DSP and media partner relationships, drive cross-functional workstreams, forecast adoption, and ensure early adopter success and product positioning for life sciences advertisers.

Lead design and delivery of production AI Agent features for Veeva QualityDocs and Training. Define data flows, model integration, orchestration, and prompts; collaborate with engineering and UX to automate regulated quality and training processes; evaluate AI agents and present capabilities to stakeholders.