Top Tech Jobs & Startup Jobs

Senior engineer who will found and grow an AI-first product team, own feature lifecycle from design to production support, drive scalable SaaS architecture, mentor engineers, perform expert code reviews, and define engineering best practices using AI-assisted tooling.

Build and own features for a new AI-driven enterprise SaaS platform for life sciences. Design, develop, deploy, and support production Python services, collaborate on technical design, drive scalability, mentor engineers, and define engineering best practices with AI-assisted workflows.

Lead design and implementation of cloud-native DevOps for a new AI-driven platform. Build IaC, CI/CD pipelines, automate deployments, provision and scale infrastructure, improve reliability, and drive engineering best practices and mentorship.

Lead DevOps engineering for a new AI-driven life sciences platform: design cloud architecture, implement IaC, build CI/CD pipelines, manage Kubernetes/OpenShift and serverless infrastructure, improve reliability and performance, and mentor the growing engineering team.

Lead design and implementation of cloud-native infrastructure and DevOps practices for a new AI-driven life sciences platform. Build IaC, CI/CD pipelines, and automated deployments; manage and scale infrastructure with Ansible, Terraform, and Kubernetes; improve reliability, performance, and operational risk; mentor engineers and drive architectural best practices.

Manage and develop the Product Support team, ensuring exceptional technical assistance for Veeva applications and maintaining customer satisfaction.

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.