Top Artificial Intelligence Jobs

Design, build, and deploy AI/ML and generative AI solutions for internal teams and biopharma clients. Integrate AI APIs, create prototypes and production applications, develop data pipelines, and deploy scalable cloud-based systems. Build client-facing tools, dashboards, and intelligent services while evaluating emerging AI technologies. Collaborate with cross-functional teams, provide technical guidance, gather requirements, support platform rollouts, and promote responsible AI, LLM, RAG, prompt engineering, and agent best practices.

Manage full sales cycle to acquire and grow nonprofit customers, build relationships with decision-makers, close SaaS deals, share market feedback, and hit revenue targets while supporting existing accounts.

Manage full sales cycle to grow nonprofit customers, build relationships with decision-makers, close deals, expand accounts, share market insights, and hit revenue targets.

Design and deploy generative AI workflows and multi-agent architectures for healthcare applications. Curate EHR and claims data, extract clinical variables from unstructured medical text, and develop evaluation pipelines for agent safety, accuracy, factuality, and compliance. Apply advanced machine learning, NLP, and LLM techniques to create trustworthy longitudinal datasets supporting autonomous care agents and clinical decision tools. Communicate technical findings to technical and non-technical stakeholders.

Lead the architecture and technical strategy of Stord’s AI platform while building agent orchestration, tool systems, prompt management, integrations, and stateful edge services. Ship reliable LLM-powered features, guide AI-assisted development, establish engineering quality standards, mentor engineers, manage technical risks, and collaborate with product, data science, ML, and engineering teams.

Lead the design, development, deployment, and maintenance of machine learning models for personalization, recommendations, churn prediction, lifetime value, advertising, and business insights. Own the full data science lifecycle, analyze complex datasets, collaborate with product, engineering, editorial, and revenue teams, mentor junior staff, and promote advanced data science practices.

Own an AI finance product vertical end-to-end, including strategy, metrics, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, reconciliation, reliability, security, and scalability. Incorporate regulatory requirements across KYC, monitoring, limits, privacy, and licensing. Apply AI with evaluation, safeguards, human oversight, and failure handling while aligning compliance, operations, treasury, finance, and design.

Leads the technical foundation for BioMarin’s Patient FIND capability, developing reusable, governed healthcare data products, analytical datasets, feature logic, quality controls, lineage, and measurement layers. Translates strategic priorities into technical requirements and scalable roadmaps, enables AI/ML and commercial analytics, and coordinates engineering, data science, governance, medical, commercial, and external teams. The role provides senior technical leadership, resolves data and compliance issues, mentors contributors, and supports future organizational capability building.

Leads technical and writing teams delivering generative AI products, coordinating customers, data, product, and research teams. Tracks annotator metrics, manages labeling initiatives, creates prompts and responses, develops stakeholder guidelines, and trains teams on LLM and dataset best practices. The role includes customer interaction, quality assurance, and exposure to potentially toxic or sensitive content.

Own an AI stockbroking product vertical end-to-end, including strategy, metrics, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, reconciliation, security, scalability, and failure handling. Incorporate KYC, transaction monitoring, privacy, licensing, and regulatory requirements. Apply AI with evaluation, safeguards, human oversight, and reliability controls while coordinating Engineering, Design, Compliance, Operations, Treasury, and Finance.

Build and shape an agent-orchestration platform using frontier LLMs. Transform heterogeneous enterprise program data into structured, queryable knowledge, develop reliable and observable backend services, and own features from design through production. Collaborate with product management and customers, make prioritization decisions, review code, write tests, and support production systems. The role requires strong Python backend skills, LLM production experience, cloud expertise, and comfort solving ambiguous startup problems.

Own an AI finance product vertical end to end, including strategy, metrics, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, reliability, security, and scalability. Incorporate regulatory requirements such as KYC, transaction monitoring, limits, privacy, and licensing. Apply AI with evaluation frameworks, safeguards, human oversight, and failure handling while coordinating Engineering, Design, Compliance, Operations, Treasury, and Finance.

Own a financial product vertical end to end, including strategy, metrics, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, reconciliation, security, scalability, and failure handling. Embed regulatory requirements across KYC, transaction monitoring, limits, privacy, and licensing. Apply AI with appropriate evaluation, safeguards, human oversight, and reliability controls while coordinating Engineering, Design, Compliance, Operations, Treasury, and Finance.

Own an AI stockbroking product vertical end-to-end, including strategy, metrics, roadmap, technical design, delivery, regulatory requirements, AI evaluation, reliability, and launch. Partner with engineering, compliance, operations, finance, treasury, and design to build reliable financial products across payments, trading, wealth, and related services. Ensure accurate funds handling, trusted AI features, regulatory compliance, and effective execution in a distributed global team.

Own an AI neobank product vertical end-to-end, including strategy, roadmap, technical design, delivery, and launch. Partner with engineering across APIs, data flows, ledgering, reconciliation, security, and scalability. Incorporate KYC, transaction monitoring, privacy, licensing, and regulatory requirements. Apply AI with evaluation, safeguards, human oversight, and failure handling while coordinating Engineering, Design, Compliance, Operations, Treasury, and Finance.

Build and lead an AI-native consumer investing business, defining its proposition, roadmap, business model, and investment experiences. Own P&L, assets, customers, engagement, revenue, and unit economics while partnering with product, engineering, and AI teams. Build investing, product, technology, and commercial teams; scale the business into new investment products and markets; and use AI to improve investment research, decision-making, and portfolio management.

Own an AI investing product vertical end to end, including strategy, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, reconciliation, reliability, security, and scalability. Incorporate regulatory requirements such as KYC, transaction monitoring, limits, privacy, and licensing. Apply AI with evaluation, safeguards, human oversight, and failure handling while coordinating engineering, compliance, operations, finance, and external partners.

Own an AI neobank product vertical end to end, including strategy, metrics, roadmap, technical design, delivery, and launch. Shape systems involving APIs, data flows, ledgering, reconciliation, security, scalability, and failure handling. Incorporate KYC, transaction monitoring, privacy, licensing, and regulatory requirements. Apply AI with evaluation, safeguards, human oversight, and reliability controls while coordinating engineering, design, compliance, operations, treasury, and finance.

Own an AI investing product vertical end-to-end, including strategy, metrics, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, reconciliation, security, scalability, and failure handling. Incorporate KYC, transaction monitoring, limits, privacy, licensing, regulatory approvals, financial rails, and third-party dependencies. Apply AI with evaluation, safeguards, human oversight, and reliability controls while aligning engineering, compliance, operations, treasury, finance, and design.

Build and own an AI-native stockbroking business, defining its proposition, roadmap, business model, and AI-powered investing experiences. The CEO will own P&L, funded accounts, assets, trading activity, revenue, and unit economics; build brokerage, custody, trading, and market infrastructure; manage strategic partnerships; lead product and engineering execution; and oversee team building, licensing, regulatory readiness, and market expansion.

Build and lead an AI-native finance business spanning spending, saving, investing, and everyday financial needs. Define product strategy, roadmap, business model, and financial workflows; launch and scale products; own P&L, growth, revenue, unit economics, and operations; collaborate with product, engineering, and AI teams; build the organization; and expand into new products and markets.

Design and lead agentic AI workflows for biologics discovery, automating secondary assay analysis and connecting lab automation, scientific data, models, and compute. Build real-time pipelines, resilient APIs, workflow orchestration, observability, and production integrations. Enable closed-loop design-make-test-learn feedback through high-quality, traceable, AI-ready data. Partner with discovery, data science, GenAI, ontology, MLOps, and infrastructure teams, while setting technical direction, evaluating emerging technologies, and mentoring engineers.

Design and build scalable enterprise applications in C#/.NET (APIs, microservices) and integrate AI capabilities (Python, LLMs, RAG, vector DBs, agentic frameworks). Own CI/CD, Azure DevOps workflows, containerized deployments, and collaborate across teams to deliver AI-enabled operational automation and agent integrations.

Build and lead an AI-native stockbroking business, defining its proposition, product roadmap, business model, and AI-powered investing experiences. Own P&L, growth metrics, trading activity, revenue, and unit economics. Develop brokerage, custody, trading, and market infrastructure; manage strategic partnerships; collaborate with product, engineering, and AI teams; build the leadership team; and oversee licensing, regulatory readiness, and international expansion.

Own the end-to-end strategy, roadmap, metrics, backlog, technical design, regulatory readiness, and launch of an AI-powered investing product. Partner with engineering, compliance, operations, treasury, finance, and design to ensure correct money movement, resilient integrations, trusted AI behavior, and compliant releases. The role requires strong technical product leadership, system design expertise, regulated-domain experience, and hands-on understanding of LLM evaluation and risk management.