Jobs at Visium

Advise C-level life sciences and healthcare executives on AI and data strategies, lead large-scale digital transformations, develop scalable solutions, oversee high-quality consulting delivery, build long-term client relationships, generate new business, and manage cross-functional engagement teams and multimillion-dollar client portfolios.

Advise C-level life sciences and healthcare executives on AI and data strategies, lead large-scale digital transformations, develop client solutions, and guide implementation and scaling. Build new business opportunities, manage long-term client relationships and multimillion-dollar portfolios, lead cross-functional engagement teams, and ensure high-quality analytical deliverables. Contribute to practice development and organizational growth.

Advise C-level life sciences and healthcare executives on AI and data strategies, lead large-scale digital transformations, develop client relationships, generate consulting business, oversee major client portfolios, and guide cross-functional teams in designing, implementing, and scaling AI and data solutions.

Own Visium's internal AI strategy and operations: build and govern agentic workflows, deploy and manage the AI tool stack, drive adoption through enablement and change management, measure impact and ROI, and favor pragmatic build-vs-buy decisions.

You will design, build, and maintain agentic architectures and multi-agent systems for AI products in the pharmaceutical domain, focusing on compliance and scalability.

As a Lead Data Engineer, you will design, build, and maintain scalable data platforms, assess data landscapes, and collaborate with stakeholders to translate requirements into robust data solutions.

Serve as the bridge between engineering and business to deliver AI products from PoC to production. Translate business needs into product requirements, manage planning and prioritization, challenge technical decisions for scalability, mitigate risks and dependencies, and maintain stakeholder alignment and delivery cadence across cross-functional teams.

The Staff AI Engineer will lead complex ML projects, mentor engineers, and drive adoption of ML best practices while ensuring architectural excellence. This role balances hands-on coding with strategic leadership and client collaboration.

Design and deliver end-to-end AI solutions from proof-of-concept to production on Azure. Architect GenAI, RAG, AI agents and ML systems, define standards and governance, guide engineering teams on MLOps/LLMOps, security and deployment, evaluate emerging AI technologies, and mentor engineers.

Define and drive architecture for end-to-end AI and data platforms on Azure. Establish standards, governance, and scalable cloud-native AI solutions; evaluate emerging AI technologies; translate business needs into technical designs; mentor engineering and data teams; ensure platform performance, security, and compliance.

As an AI Software Engineer, you will lead AI software projects, mentor colleagues, collaborate with stakeholders, and drive best practices in software engineering.

The Senior Data & AI Strategist will lead data and AI transformation initiatives, advise clients, and ensure impactful strategy delivery, while mentoring team members.

Lead complex machine learning projects, mentor engineers, ensure architectural excellence, and drive strategic initiatives while contributing high quality code.

As a Machine Learning Engineer, you'll apply state-of-the-art techniques to projects, enhance customer experiences, and communicate results effectively.

Design and lead scalable, secure Azure-based data platforms and architectures. Define data models, standards, governance, and best practices. Guide technical trade-offs, collaborate with engineering and analytics teams, ensure performance, security, and cost-efficiency, and contribute to long-term data strategy and platform evolution.

Design, build, and maintain cloud-native platforms, data pipelines, warehouses/lakehouses, and platform components. Ensure security, reliability, scalability, and collaborate across teams to define architecture and standards supporting AI and analytics.

Join the AI Engineering team to design, build, deploy, and scale production AI systems. Translate business problems into AI solutions, industrialize ML models, design AI pipelines and platforms, ensure performance and monitoring, and drive MLOps best practices across architecture and governance.

As a Senior AI/ML Engineer, you will develop and deploy AI initiatives, focusing on ML solutions and ensuring robust software integration. Responsibilities include coding, MLOps implementation, Agile delivery, and collaboration with stakeholders to translate business needs into technical solutions.

As an AI Machine Learning Engineer, you'll develop and deploy AI solutions, implement MLOps workflows, and partner with stakeholders to translate business challenges into technical requirements.

Lead AI engineering initiatives by establishing platform strategies, managing talent, enforcing technical standards, and ensuring the operational excellence of AI products.