Development Manager

Veeva Systems is a mission-driven organization and pioneer in industry cloud, helping life sciences companies bring therapies to patients faster. As one of the fastest-growing SaaS companies in history, we surpassed $3B in revenue in our last fiscal year with extensive growth potential ahead.

At the heart of Veeva are our values: Do the Right Thing, Customer Success, Employee Success, and Speed. We're not just any public company – we made history in 2021 by becoming a public benefit corporation (PBC), legally bound to balancing the interests of customers, employees, society, and investors.

Join us in transforming the life sciences industry, committed to making a positive impact on its customers, employees, and communities.

We are looking for an experienced and technically rigorous Development Manager to lead the end-to-end engineering and product delivery of our core software solutions. In this role, you will bridge technical architecture with product vision across modern tech stacks (Python, Java, Vue.js, and multi-cloud environments) while driving the practical integration of Generative AI across the SDLC. Additionally, you will champion the operationalization of production-grade AI Agents and custom Skills to power intelligent product capabilities.

Team Leadership & Talent Development: Lead capacity planning, recruitment, onboarding, and structure of the engineering team; mentor developers, technical workshops, and career development frameworks to foster engineering excellence.

Architecture & Engineering Delivery: Direct end-to-end technical selection and system architecture across Python, Java, and Vue.js frameworks, ensuring software systems are modular, highly scalable, and secure.

AI-Augmented SDLC Integration: Champion and embed AI tooling directly into the Software Development Life Cycle (SDLC)—including automated testing, code review workflows, and developer productivity tooling—to measurably boost engineering velocity and code quality.

Agent & Skill Productization: Architect and deliver production-grade AI Agents and custom extensible Skills/Tools, leveraging patterns such as Function Calling, RAG (Retrieval-Augmented Generation), and memory management to solve complex business scenarios.

Cloud & Infrastructure Governance: Design and govern resilient cloud architectures on AWS and Alibaba Cloud, overseeing containerization, service orchestration, and high-throughput middleware systems (e.g., Kafka, RabbitMQ, Redis).

Data Modeling & Standards: Establish enterprise data modeling standards (conceptual, logical, and physical), lead database schema optimization, and ensure consistent, high-performance data access across relational and non-relational storage engines.

Cross-Functional Delivery: Partner closely with Product Managers, algorithm engineers, QA, and domain specialists to manage agile sprints (Scrum/Kanban), mitigate technical risks, and ensure predictable, high-quality milestone delivery.

Experience: Bachelor’s degree in Computer Science, Software Engineering, or a related field; 5+ years of software development and system architecture experience, with 2+ years of technical team leadership or project management experience.

Technical Stack: Deep proficiency in Python and/or Java with solid hands-on engineering experience in the other; proven expertise with Vue.js (Vue 2/3, Pinia/Vuex) and enterprise frameworks (such as Spring Boot/Cloud, FastAPI, or Django).

Cloud & Middleware: Strong working knowledge of cloud-native services on AWS (e.g., ECS/EKS, RDS, S3) and/or Alibaba Cloud (e.g., ACK, RDS, OSS), alongside in-depth experience configuring and tuning middleware (Redis, Kafka, RabbitMQ).

AI in SDLC Practice: Demonstrated hands-on track record of integrating AI tools into daily SDLC workflows (e.g., GitHub Copilot, Cursor, internal DevOps bots) with measurable gains in delivery efficiency.

AI Agent & Skill Development: Practical experience designing and deploying production-level AI Agents or custom agentic skills, utilizing frameworks such as LangChain, LlamaIndex, Dify, or Semantic Kernel, with solid command of tool calling and prompt engineering.

Data Systems & Modeling: Proven mastery of database schema design and data modeling specifications across mainstream relational (MySQL, PostgreSQL) and NoSQL databases, including indexing, query optimization, and high-concurrency storage strategies.

Leadership & Communication: Exceptional problem-solving and architectural governance skills, with the ability to articulate complex technical concepts to non-technical stakeholders and translate business goals into actionable engineering roadmaps.

Domain Expertise: Professional software development background in Life Sciences, Biotechnology, Pharmaceuticals, Medical Devices, or Clinical Healthcare informatics.

Compliance & Data Standards: Familiarity with healthcare/life science data standards and regulatory compliance frameworks (e.g., GxP, HIPAA, HL7/FHIR, healthcare data anonymization/security).

Advanced AI & Vector Data: Hands-on exposure to Vector Databases (e.g., Milvus, pgvector, Pinecone) or experience implementing multi-agent coordination architectures.

Grants for fitness, communication and heating

Healthy, free, provided snacks