Full-Time

Principal Solutions Architect

Lab Orchestration

Updated on 9/4/2026

Dotmatics

Dotmatics

501-1,000 employees

Cloud-based R&D informatics for life sciences

Compensation Overview

$121.5k - $164.4k/yr

+ Variable pay + 401(k) match

Remote in USA

Remote

Category
Solution Engineering (1)
Required Skills
ERP
Distributed Systems
Observability
REST APIs
Siemens Teamcenter
Databricks

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Requirements
  • At least 10 years of experience scoping automated scientific workflow-based solutions and designing enterprise-grade SaaS or hybrid architectures.
  • Advanced understanding of integration patterns, application programming interfaces, data pipelines, and distributed systems, including event-driven architectures for real-time instrument and automation data.
  • Experience with Databricks and Apache NiFi.
  • Ability to reason about performance, scalability, and failure modes across heterogeneous, multi-system environments.
  • Familiarity with SiLA2, LADS, and OPC-UA laboratory automation connectivity standards and protocols.
  • Experience integrating complex application landscapes such as ELN, LIMS, SDMS, PLM, ERP, MES, instrument data systems, and laboratory automation schedulers across heterogeneous customer IT and operational technology environments.
  • Understanding of how digital workflow systems connect to physical laboratory execution.
  • Knowledge of scientific research and development workflows and data, particularly in life sciences, pharmaceutical or biotechnology, or regulated laboratory environments.
  • Ability to explain complex architectural decisions and digital-physical integration trade-offs to scientific, IT, and operational audiences.
  • Experience working with system integrators or technology partners in enterprise delivery models.
  • Ability to define implementation guardrails and balance enablement with governance in partner-led engagements.
Responsibilities
  • Act as the design authority for Luma-based customer solutions, including end-to-end laboratory orchestration architectures spanning scientific informatics, data infrastructure, and physical laboratory systems.
  • Define logical and physical architectures covering applications, data, integrations, identity, environments, and operations.
  • Architect solutions connecting experiment planning, protocol authoring, and scheduling through execution on automated instruments, workcells, and robotic platforms.
  • Ensure architectural consistency across multiple customer engagements.
  • Shape functional requirements with Scientific Architects and Application Scientists, including workflow automation from study design through instrument-level execution.
  • Own non-functional requirements covering performance, scalability, security, resilience, observability, accessibility, internationalization, and maintainability.
  • Translate business and scientific needs into robust technical architectures.
  • Design integration approaches using Apache NiFi, APIs, batch pipelines, and event-driven patterns.
  • Define data ingestion, transformation, and migration strategies for high-frequency, heterogeneous data from automated laboratory environments.
  • Architect experiment workflows from planning through scheduling, execution, and data capture using Luma as the orchestration layer.
  • Define integration patterns with laboratory automation and scheduling platforms.
  • Architect Databricks solutions, including configuration through Databricks SQL, for large-scale aggregation and analysis of instrument and experimental data.
  • Ensure data lineage, auditability, and regulatory compliance across the experimental data lifecycle.
  • Support visualization and analytics patterns using Sigma for Databricks.
  • Architect Luma solutions integrating with ELNs, LIMS, SDMS, PLM, ERP, MES, instrument data systems, and laboratory automation schedulers.
  • Define how Dotmatics fits within broader Siemens landscapes where scientific research and development intersects with industrial and manufacturing processes.
  • Scope and design integrations with third-party scientific platforms, scientific data analysis tools, and laboratory automation platforms.
  • Define sample tracking, workcell scheduling, and instrument connectivity architectures.
  • Apply security best practices covering IAM, data protection, tenancy, and compliance.
  • Design for high availability, resilience, and disaster recovery.
  • Define observability strategies covering logging, monitoring, alerting, automated laboratory execution environments, and instrument connectivity layers.
  • Ensure architectures are operable by support and cloud teams after go-live.
  • Act as a senior technical advisor to customers, including IT leadership, enterprise architects, and laboratory automation and informatics leads.
  • Partner with Sales and PreSales during solution shaping, scoping, risk assessment, and technical qualification of laboratory orchestration opportunities.
  • Represent Dotmatics architecture in joint Siemens engagements and architecture forums.
  • Work with Siemens and non-Siemens partners as a peer architect to ensure architectural alignment across joint delivery models.
  • Provide architectural guidance to Solution Architects, Technical Leads, Application Scientists, and Delivery Partners.
  • Review designs and implementations for architectural compliance.
  • Raise architectural maturity across the Dotmatics Professional Services organization and partner ecosystems.
  • Create reusable architectural artifacts, including reference architectures, laboratory orchestration integration templates, instrument connectivity patterns, and design decision frameworks.
  • Act as the architectural authority for partner-led implementations of the Dotmatics Luma platform.
  • Enable system integrators, Siemens partners, and regional delivery partners through architectural guidance, design reviews, and technical enablement sessions.
  • Define reference architectures, integration patterns, and implementation guardrails for partners, including digital-physical integration scope and instrument connectivity standards.
  • Support partner onboarding by defining how Luma should be implemented from architectural and non-functional perspectives.
  • Ensure partner-delivered solutions meet Dotmatics and Siemens standards for scalability, security, operability, and maintainability.
  • Collaborate with Partner, Sales, and Services leadership to define where Dotmatics retains architectural ownership.
  • Act as an escalation point for complex architectural issues arising in partner-led engagements.
Desired Qualifications
  • Architecture certifications such as TOGAF or cloud architecture certifications.
  • Experience in regulated environments involving GxP, FDA, ISO, SOC 2, or GDPR, including 21 CFR Part 11 and ALCOA+ data integrity requirements for automated laboratory systems.
  • Exposure to Siemens digital industry products such as Opcenter, Teamcenter, SIMATIC, or Industrial IoT/MindSphere.
  • Familiarity with laboratory automation scheduling platforms such as Green Button Go, Momentum, Overlord, Cellario, or SAMI, and with liquid handling or instrument vendor ecosystems.

Dotmatics provides a cloud-based R&D software platform for life sciences, chemistry, biology, and materials research, unifying data management, workflow automation, and analytics. Its suite includes GraphPad Prism, SnapGene, and Geneious, plus Luma, a low-code platform for multimodal drug discovery, to capture, analyze, and share experimental data. The platform automates tasks such as instrument data ingestion, electronic lab notebooks, assay analysis, and dashboard reporting, harmonizing data across labs to boost collaboration and speed discovery. In 2025, Dotmatics was acquired by Siemens and integrated into Siemens Digital Industries Software, expanding Siemens' AI-driven product lifecycle capabilities in life sciences.

Company Size

501-1,000

Company Stage

Acquired

Total Funding

$106M

Headquarters

Boston, Massachusetts

Founded

2005

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Simplify Jobs

Simplify's Take

What believers are saying

  • Luma Agent launched May 13, 2026, automating analysis, reports, and workflow configuration.
  • LabArchives for Government won FedRAMP authorization April 30, 2025, unlocking federal research sales.
  • Bioinformatics spending is surging; BCC Research projects $43.5 billion market value by 2030.

What critics are saying

  • Benchling, Veeva, and Dassault target the same lab-informatics stack, pressuring renewals by 2027.
  • Siemens integration can bury Dotmatics under PLM priorities, slowing product velocity and hiring.
  • Life-sciences AI agents face governance failures; one bad audit trail can kill enterprise deployments.

What makes Dotmatics unique

  • Dotmatics owns GraphPad Prism, SnapGene, Geneious, and Luma across 10,000 organizations.
  • Siemens completed Dotmatics acquisition July 1, 2025, embedding science into Xcelerator.
  • Luma runs natively on Databricks, linking scientific context with governed enterprise AI.

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Benefits

Remote Work Options

Unlimited Paid Time Off

Flexible Work Hours

401(k) Retirement Plan

401(k) Company Match

Health Insurance

Health Savings Account/Flexible Spending Account

Dental Insurance

Vision Insurance

Paid Vacation

Paid Holidays

Sabbatical Leave

Hybrid Work Options

Stock Options

Company Equity

Wellness Program

Mental Health Support

Gym Membership

Phone/Internet Stipend

Home Office Stipend

Conference Attendance Budget

Professional Development Budget

Family Planning Benefits

Fertility Treatment Support

Adoption Assistance

Parental Leave

Parental Leave

Family Planning Benefits

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

0%

2 year growth

-1%
Mining Press Releases
Aug 7th, 2026
Bioinformatics market to reach $43.5 billion by 2030, driven by AI integration and Expanding genomics applications.

Bioinformatics market to reach $43.5 billion by 2030, driven by AI integration and Expanding genomics applications. "According to BCC Research, the global bioinformatics market is projected to grow from $23.5 billion in 2025 to $43.5 billion by 2030, at a CAGR of 13.1%, driven by exponential growth in biological and genomic data, expanding precision medicine and the integration of AI-powered analytics across life sciences research and drug discovery." Boston, Aug. 07, 2026 (GLOBE NEWSWIRE) - The global bioinformatics market is projected to grow from $20.9 billion in 2024 to $43.5 billion by 2030, advancing at a compound annual growth rate (CAGR) of 13.1% during the 2025-2030 forecast period. This analysis is detailed in Bioinformatics: Technologies and Global Markets, a newly published report by BCC Research examining the computational tools, software platforms, and services reshaping biological research and drug development worldwide. Key Findings - Market Scale and Momentum: The bioinformatics market is on track to more than double in value over six years, underpinned by surging demand across genomics, proteomics, and data-intensive biological research disciplines. The convergence of next-generation sequencing (NGS), multi-omics platforms, and AI-driven analytics is accelerating investment in computational biology infrastructure at a pace that outstrips broader life sciences sector growth. - North America Leads Global Adoption: North America commands 47.7% of the global bioinformatics market, reflecting deep institutional investment in genomic research, a mature biopharma ecosystem, and robust venture capital activity in digital biology. The region's dominance is further reinforced by proximity to leading technology vendors and a concentration of top-tier academic research centers. - AI and Cloud Computing Redefine the Toolkit: The integration of artificial intelligence, machine learning, and cloud-based deployment into bioinformatics workflows is fundamentally restructuring the competitive landscape. AI-driven modeling now enables ADMET profile predictions that compress preclinical timelines, while pay-as-you-go cloud services are democratizing access to high-performance computing resources across geographies and institution sizes. - Personalized Medicine and Oncology as Structural Growth Engines: Increasing demand for personalized medicine and targeted cancer therapies is a defining demand-side driver. Growing oncology research funding is accelerating bioinformatics adoption specifically for tumor genomics, biomarker identification, and treatment stratification - areas where computational analysis has moved from supplementary to mission-critical. - Emerging Technologies Expanding the Frontier: Long-read sequencing platforms such as PacBio HiFi, single-cell multiomics, quantitative high-throughput screening combined with machine learning, and national bio data platforms - including South Korea's initiative targeting millions of genomic data cases by 2035 - represent the next wave of bioinformatics capability. Digital twin technology and AI-powered software, as evidenced by Siemens' acquisition of Dotmatics, signal increasing convergence between industrial informatics and life sciences. - Competitive Landscape: Key participants shaping the global bioinformatics market include Illumina Inc., Thermo Fisher Scientific Inc., Agilent Technologies Inc., Dassault Systèmes, Bio-Rad Laboratories Inc., Siemens Healthineers AG, PacBio, Revvity, DNASTAR, Qlucore AB, Molecular Networks GmbH, MacVector Inc., Real Time Genomics, and Excelra. Market Drivers The bioinformatics market is being propelled by the exponential growth of data generated through high-throughput sequencing, imaging, and multi-omics studies, creating urgent demand for scalable storage systems, advanced analytical platforms, and specialized talent. Public funding mechanisms - including France 2030, Horizon Europe, and UKRI programs - are providing critical infrastructure support, while public-private collaborations such as the BD Biosciences and CSIR-IGIB single-cell multiomics Centre of Excellence in India are extending capacity into emerging economies. The uptake of NGS technologies and cloud services in markets such as China further broadens the global addressable opportunity. Cheminformatics is emerging as a particularly dynamic sub-segment, with AI-driven modeling enabling drug discovery teams to predict toxicity profiles and prioritize candidates with greater precision and speed. Open-source tools including RDKit and Bioclipse are simultaneously lowering the barrier to entry for academic and smaller commercial institutions, widening adoption across the research ecosystem. Investment Considerations Investors evaluating bioinformatics exposure should consider that the sector sits at the intersection of two durable megatrends: the digitization of biology and the industrialization of drug discovery. The highest-conviction opportunities lie with platform companies capable of integrating multi-omics data at scale - particularly those embedded in oncology workflows and personalized medicine pipelines where switching costs are high and regulatory tailwinds are favorable. Key risks include the substantial cost of advanced software licensing, a constrained and expensive bioinformatics talent pool - with U.S. and European salaries ranging from $90,000 to over $110,000 annually as of 2026 - and regulatory complexity around genomic data privacy across jurisdictions including China's PIPL, India's DPDP Act, and Japan's APPI. Companies with diversified geographic exposure and cloud-native architectures are best positioned to navigate this fragmented compliance environment. Uneven regional adoption, particularly across Latin America, presents a longer-dated but meaningful expansion opportunity. About the Report Bioinformatics: Technologies and Global Markets provides comprehensive market sizing, segmentation by technology and application, competitive intelligence, and a forecast spanning 2025-2030 across global and regional dimensions. About BCC Research BCC Research provides objective, unbiased measurement and assessment of market opportunities with detailed market research reports. Our experienced industry analysts assess growth trends, identify and evaluate new and changing market opportunities, and provide critical information and innovative decision support tools to help inform the strategic decision-making process. For media inquiries, email [email protected] or visit our media page for access to our market research library. Any data and analysis extracted from this press release must be accompanied by a statement identifying BCC Research LLC as the source and publisher. BCC Research LLC 50 Milk St., Ste. 16, Boston, MA 02109 [email protected] | +1 781-489-7301 www.bccresearch.com Legal Disclaimer: EIN Presswire provides this news content "as is" without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the author above.

StartupHub AI
Jul 17th, 2026
Dotmatics Luma, Databricks forge AI-Ready Science.

Dotmatics Luma, Databricks forge AI-Ready Science. Dotmatics Luma and Databricks team up to transform siloed scientific data into a unified, AI-ready resource for faster research insights. Visual TL;DR. Siloed Scientific Data causes Lost Data Context. Siloed Scientific Data addressed by Dotmatics Luma. Dotmatics Luma integrates with Unified Scientific Stack. Databricks Platform integrates with Unified Scientific Stack. Unified Scientific Stack enables AI-Ready Science. AI-Ready Science leads to Faster Research Insights. * Siloed Scientific Data: vast amounts of research data trapped in isolated systems, losing context * Lost Data Context: integrity compromised as data moves, leading to untrustworthy AI models * Dotmatics Luma: scientific operating layer capturing and harmonizing instrument outputs in real time * Databricks Platform: enterprise-grade infrastructure for storing, managing, and activating harmonized data at scale * Unified Scientific Stack: merging Luma's data capabilities with Databricks' enterprise infrastructure * AI-Ready Science: transforming fragmented data into a unified, actionable resource for AI applications * Faster Research Insights: accelerating discovery through streamlined workflows and reliable AI models Visual TL;DR Scientific research generates vast amounts of data, often trapped in silos. Databricks and Dotmatics are partnering to bridge the gap between raw experimental output and actionable scientific insight. The core challenge lies in maintaining data context and integrity as it moves across instruments and analyses. When this context is lost, AI models trained on fragmented data yield untrustworthy results.

PR Newswire
May 13th, 2026
Dotmatics launches Luma Agent, an AI co-scientist that executes complex scientific work and configures platforms

Dotmatics has launched Luma Agent, an agentic AI capability embedded in its Luma Scientific Intelligence Platform, valued at $1.45 billion. The AI co-scientist plans and executes complex scientific tasks using natural language, including analysing data, generating reports and configuring the platform itself. Built on structured, ontology-backed scientific data, Luma Agent enables scientists to complete work in minutes that previously took days. Every action is logged with full audit trails and requires human approval before data changes, addressing governance requirements that Gartner predicts will halt 80% of agentic AI initiatives in healthcare and life sciences in 2026. The system allows scientists and administrators to configure data models and workflows through conversation, eliminating the need for specialist service engagements. Luma Agent integrates with external AI tools via Model Context Protocol.

Siemens
Sep 17th, 2025
Siemens completes acquisition of Dotmatics

Siemens AG announced today that it has completed the acquisition of Dotmatics, a leading provider of Life Sciences R&D software headquartered in Boston and port

U.S. Securities and Exchange Commission
Jul 16th, 2025
SEC FORM D

The Securities and Exchange Commission has not necessarily reviewed the information in this filing and has not determined if it is accurate and complete.The reader should not assume that the information is accurate and complete.