Top Tech Jobs & Startup Jobs

Lead and consolidate Evinova’s distributed testing teams into a unified quality engineering function. Establish testing standards, GA-readiness criteria, automation roadmaps, CI/CD integration, quality metrics, GxP traceability, audit readiness, and AI evaluation practices. Build the leadership structure, improve automation maturity, oversee multi-product release quality, and embed AI-assisted testing across engineering and product delivery.

Develops outbound pipeline among pharma, biotech, and CRO accounts through multichannel prospecting, account research, discovery calls, lead qualification, and opportunity progression. Maintains Salesforce data, follows up on inbound and event leads, partners with Marketing, Sales, and Product, and shares market insights. Represents Evinova at industry events while managing complex, lengthy sales cycles involving multiple stakeholders.

Director-level AI Engineer responsible for setting technical direction and delivery standards across Generative AI, AI Agent, and Digital Twin initiatives. The role defines architectures and playbooks, reviews designs and code, guides production deployment, advises stakeholders, manages technical risks, evaluates emerging technologies, and mentors engineers across teams without direct reports. Requires deep hands-on expertise in Python, agentic AI, software development, and scalable production systems, along with strong technical leadership and stakeholder influence.

Build and operate production-grade machine learning, data engineering, and agentic AI systems for commercial analytics in rare disease. Responsibilities include Snowflake data pipelines, model deployment, CI/CD, monitoring, prompt and agent workflow design, governance, security, compliance, testing, documentation, and enterprise integrations. The role partners with data scientists and commercial stakeholders to deliver scalable, auditable AI capabilities in a regulated healthcare environment.

Lead the transformation of low-code analytics into scalable pro-code applications. Build React and TypeScript front ends, Python and FastAPI services, REST APIs, data integrations, testing, and CI/CD pipelines. Coach developers transitioning to pro-code, establish reusable engineering patterns, and promote responsible AI-assisted development. Manage technical risks, performance, quality, governance, adoption metrics, and cross-functional delivery across the software development lifecycle.

Owns the roadmap, operations, vendor relationships, governance, costs, and user enablement for cancer genomics, single-cell, and spatial analytics platforms. The role coordinates scientists, engineers, vendors, procurement, and finance; ensures FAIR data practices, privacy, security, service levels, integrations, AI governance, and regional deployments; and manages platform renewals, incidents, releases, documentation, and financial planning.

Own the R&D agentic AI platform, including its roadmap, skills marketplace, data connectors, governed access, onboarding, support, usage metrics, and cost management. Partner with AI scientists, engineers, security, architecture, data owners, finance, and enterprise platform teams to prioritize work, define requirements, manage risks, and deliver a consistent user experience in a regulated environment.

Leads AstraZeneca’s enterprise technology architecture and strategy across cloud, data, AI, platforms, and digital products. Establishes architectural guardrails, reusable platforms, AI capabilities, API-first patterns, and internal developer experiences. Advises executive stakeholders, drives transformation and modernization, embeds security and regulatory compliance, and develops a global architecture and technology leadership community. Success includes faster decisions, increased platform reuse, greater AI adoption, improved developer productivity, and reduced complexity and cost.

Lead hands-on engineering for AstraZeneca’s APD Platform, designing and operating scalable data pipelines, data products, AI applications, and machine learning capabilities. Responsibilities include data integration, governance, quality, lineage, MLOps, generative AI, DevOps, cloud engineering, architecture, technical standards, mentoring, and stakeholder collaboration. The role supports secure, reliable, and reusable capabilities for pharmaceutical R&D while providing technical leadership across multidisciplinary teams.

Leads the U.S. Oncology CRM product strategy and technical activation of Salesforce Life Science Cloud, Marketing Cloud, Data Cloud, and Agentforce. Translates business needs into scalable architectures, modernizes integrations through API-first and event-driven designs, and enables AI-driven omnichannel engagement. Partners with global product teams, leads engineering squads, governs vendors, and establishes DevSecOps, delivery, quality, and architecture standards. The role requires deep Salesforce, CRM, integration, data, agile leadership, and oncology domain expertise.