TetraScience

Role Description We’re looking for a Senior AI Platform Engineer to help design, build, and scale our AI and data infrastructure. In this role, you’ll focus on architecting and maintaining cloud-based MLOps pipelines to enable scalable, reliable, and production-grade AI/ML workflows, working closely with AI engineers, data engineers, and platform teams. Your expertise in building and operating modern cloud-native infrastructure will help enable world-class AI capabilities across the organization. If you are passionate about building robust AI infrastructure, enabling rapid experimentation, and supporting production-scale AI workloads, we’d love to talk to you. - Design, implement, and maintain cloud-native platform to support AI and data workloads, with a focus on AI and data platforms such as Databricks and AWS Bedrock. - Build and manage scalable data pipelines to ingest, transform, and serve data for ML and analytics. - Develop infrastructure-as-code using tools like Cloudformation, AWS CDK to ensure repeatable and secure deployments. - Collaborate with AI engineers, data engineers, and platform teams to improve the performance, reliability, and cost-efficiency of AI models in production. - Drive best practices for observability, including monitoring, alerting, and logging for AI platforms. - Contribute to the design and evolution of our AI platform to support new ML frameworks, workflows, and data types. - Stay current with new tools and technologies to recommend improvements to architecture and operations. - Integrate AI models and large language models (LLMs) into production systems to enable use cases using architectures like retrieval-augmented generation (RAG). Qualifications - 7+ years of professional experience in software engineering and infrastructure engineering. - Extensive experience building and maintaining AI/ML infrastructure in production, including model, deployment, and lifecycle management. - Expert-level coding skills in TypeScript and Python building robust APIs and backend services. - Production-level experience with Databricks MLFlow, including model registration, versioning, asset bundles, and model serving workflows. - Expert level understanding of containerization (Docker), and hands on experience with CI/CD pipelines, orchestration tools (e.g., ECS) is a plus. - Proven ability to design reliable, secure, and scalable infrastructure for both real-time and batch ML workloads. - Strong knowledge of AWS and infrastructure-as-code frameworks, ideally with CDK. - Ability to articulate ideas clearly, present findings persuasively, and build rapport with clients and team members. - Strong collaboration skills and the ability to partner effectively with cross-functional teams. Nice to Have - Familiarity with emerging LLM frameworks for advanced prompt orchestration and programmatic LLM pipelines. - Understanding of LLM cost monitoring, latency optimization, and usage analytics in production environments. - Knowledge of vector databases / embeddings stores (e.g., OpenSearch) to support semantic search and RAG. Benefits - 100% employer-paid benefits for all eligible employees and immediate family members. - Unlimited paid time off (PTO). - 401K. - Flexible working arrangements - Remote work. - Company paid Life Insurance, LTD/STD. - A culture of continuous improvement where you can grow your career and get coaching.

• Help to hire, develop, and retain a high-performing team of Scientific Solutions Partners; set clear performance expectations and coach to both scientific credibility and commercial rigor • Establish and reinforce the operating cadence of the team — pipeline reviews, deal inspection, forecasting discipline, and account planning • Coach team members through complex, technical, multi-stakeholder sales cycles, modeling best practice on your own strategic accounts • Serve as an escalation point and executive sponsor for the team’s most important customer relationships and competitive situations • Foster a culture aligned to The Tetra Way — scientific depth, customer obsession, accountability, and high standards • Personally lead technical discovery on strategic accounts and raise the bar for how the team understands each customer’s lab data landscape — instruments, data formats, informatics stack, and data science ambitions • Design and present compelling solution architectures aligned to specific scientific use cases (e.g., ADMET assays, FPLC/UPLC chromatography, bioassay data harmonization, AI training datasets), while ensuring the team can do the same • Champion leading with demos of actual software aligned to each customer’s main value levers • Direct and quality-assure proof-of-concept and proof-of-value engagements across the team, partnering with TetraScience scientific data architects to deliver credible, high-quality demonstrations of the Tetra Scientific Data Foundry’s capabilities • Own RFP technical strategy end-to-end for marquee opportunities, and set the standard for how the team synthesizes platform capabilities, scientific use cases, and customer-specific requirements into compelling, accurate submissions • Articulate the medallion data architecture in scientific and business terms: how bronze (raw scientific data), silver (harmonized Tetra Data), and gold (analysis-ready datasets) each create value, and how TetraScience’s AI-native layer accelerates scientific outcomes • Keep the team current on the scientific and informatics landscape — relevant assay workflows, instrument vendors, SDMS/ELN/LIMS/analytical software integrations, and AI/ML use cases in drug discovery and development • Own the territory commercial strategy and number; build and manage a rigorous, accurate team pipeline with consistent forecasting and visibility to leadership • Personally prospect, qualify, and close strategic flagship accounts while driving the team’s broader pipeline generation in alignment with the TetraScience go-to-market strategy • Relentlessly identify and close expansion opportunities across new labs, instruments, geographies, sites, and use cases within existing accounts — directly and through the team • Manage and coach the full sales cycle from discovery through contracting, using modern sales methodologies (MEDDIC, MEDDPICC, Force Management, or similar) • Build and expand relationships across customer organizations at the most senior levels, from individual contributors to C-suite executive sponsors • Partner with Delivery Management to ensure smooth handoff from sales to delivery and continuity of scientific context across the team’s accounts • Represent TetraScience at industry conferences, seminars, and customer events as a senior, scientifically credible voice • Contribute customer and market insights back to product, marketing, and science teams to inform roadmap and messaging • Help develop compelling content — case studies, solution briefs, demo narratives — that advances the category and enables your team

Role Description The Director, Scientific Solutions is a senior leadership role born from a deliberate strategic choice: the most effective way to sell and scale TetraScience’s Scientific Data and AI Cloud is to have a leader who can credibly do both — win the scientific and technical confidence of the customer and own the commercial relationship through close — while leading and developing a team of Scientific Solutions Partners. No separate Account Executive needed. This is not a traditional sales-management role with a presales overlay. The Director owns the most strategic accounts in the region personally while building, coaching, and holding accountable a team of Scientific Solutions Partners. You will set commercial strategy for your territory, model the full customer engagement — from prospecting and discovery through technical solutioning, proof-of-concept, RFP response, and close — and remain accountable for the health, expansion, and renewal of the book of business alongside Delivery Management. You carry both an individual mandate on flagship accounts and a leadership mandate for your team’s collective number. You will work with the world’s largest enterprise biopharma, biotech, and life sciences companies, helping them understand how the Tetra Scientific Data Foundry and Tetra OS transform siloed, raw scientific data into AI-ready scientific datasets across the medallion architecture (bronze → silver → gold → AI-native). You and your team will engage audiences ranging from bench scientists and data engineers to CDOs, VPs of Divisional IT, VPs of Scientific areas, and digital transformation executives. TetraScience provides its solutions leaders with AI-powered tools — including Claude Cowork and Codex — that automate RFPs, triage, and contracting workflows, enabling each leader and their team to operate with the leverage of a much larger organization. Qualifications - Advanced degree in a life science, chemistry, or engineering discipline preferred (MS or PhD); equivalent practical experience considered - 12+ years of combined scientific, technical, and commercial experience in life sciences software, laboratory informatics, scientific data infrastructure, or adjacent domains - Demonstrated leadership experience — managing, coaching, or formally leading sales/solutions professionals, or strong evidence of player-coach leadership and the readiness to build and run a team - Proven track record of personally owning and closing enterprise deals while elevating the performance of others around you - Direct experience in pharma, biotech, or CRO/CDMO environments — as a scientist, scientific software professional, or sales/solutions professional serving these customers - Demonstrated ability to lead and coach complex technical sales cycles in enterprise SaaS or scientific software, including POC design and execution and RFP ownership - Deep familiarity with laboratory workflows and data: you understand what it means when a customer has 50 instruments generating unstructured data that no one can analyze - Fluency with scientific data concepts: file formats, instrument connectivity, data harmonization, and the path from raw data to AI-ready datasets - Experience with modern sales methodologies (MEDDIC, MEDDPICC, Force Management, or similar) and the ability to instill them across a team is very useful but not essential - Strong executive presence — equally compelling in a whiteboard architecture session, a C-suite business case conversation, and an internal leadership forum - Ability to travel (approximately 30%) to client sites within assigned region Requirements - Help to hire, develop, and retain a high-performing team of Scientific Solutions Partners; set clear performance expectations and coach to both scientific credibility and commercial rigor - Establish and reinforce the operating cadence of the team — pipeline reviews, deal inspection, forecasting discipline, and account planning - Coach team members through complex, technical, multi-stakeholder sales cycles, modeling best practice on your own strategic accounts - Serve as an escalation point and executive sponsor for the team’s most important customer relationships and competitive situations - Foster a culture aligned to The Tetra Way — scientific depth, customer obsession, accountability, and high standards - Personally lead technical discovery on strategic accounts and raise the bar for how the team understands each customer’s lab data landscape — instruments, data formats, informatics stack, and data science ambitions - Design and present compelling solution architectures aligned to specific scientific use cases (e.g., ADMET assays, FPLC/UPLC chromatography, bioassay data harmonization, AI training datasets), while ensuring the team can do the same - Champion leading with demos of actual software aligned to each customer’s main value levers - Direct and quality-assure proof-of-concept and proof-of-value engagements across the team, partnering with TetraScience scientific data architects to deliver credible, high-quality demonstrations of the Tetra Scientific Data Foundry’s capabilities - Own RFP technical strategy end-to-end for marquee opportunities, and set the standard for how the team synthesizes platform capabilities, scientific use cases, and customer-specific requirements into compelling, accurate submissions - Articulate the medallion data architecture in scientific and business terms: how bronze (raw scientific data), silver (harmonized Tetra Data), and gold (analysis-ready datasets) each create value, and how TetraScience’s AI-native layer accelerates scientific outcomes - Keep the team current on the scientific and informatics landscape — relevant assay workflows, instrument vendors, SDMS/ELN/LIMS/analytical software integrations, and AI/ML use cases in drug discovery and development - Own the territory commercial strategy and number; build and manage a rigorous, accurate team pipeline with consistent forecasting and visibility to leadership - Personally prospect, qualify, and close strategic flagship accounts while driving the team’s broader pipeline generation in alignment with the TetraScience go-to-market strategy - Relentlessly identify and close expansion opportunities across new labs, instruments, geographies, sites, and use cases within existing accounts — directly and through the team - Manage and coach the full sales cycle from discovery through contracting, using modern sales methodologies (MEDDIC, MEDDPICC, Force Management, or similar) - Build and expand relationships across customer organizations at the most senior levels, from individual contributors to C-suite executive sponsors - Partner with Delivery Management to ensure smooth handoff from sales to delivery and continuity of scientific context across the team’s accounts - Represent TetraScience at industry conferences, seminars, and customer events as a senior, scientifically credible voice - Contribute customer and market insights back to product, marketing, and science teams to inform roadmap and messaging - Help develop compelling content — case studies, solution briefs, demo narratives — that advances the category and enables your team Benefits - 100% employer-paid benefits for all eligible employees and immediate family members - Unlimited paid time off (PTO) - 401K - Flexible working arrangements - Remote work - Company paid Life Insurance, LTD/STD - A culture of continuous improvement where you can grow your career and get coaching

• Own documentation as a system: the pipelines that build and publish it, the AI-augmented workflows that generate drafts for human review and refinement, the review and publish process, and the infrastructure. • Lead the growth of existing docs-as-code foundation and AI-assisted documentation workflows into a docs-as-AI-agents capability. • Own documentation site and its publishing as software: docs-as-code repo, CI/CD publishing pipelines, build performance, and automated checks. • Build AI-augmented documentation workflows: drafting, summarization, classification, consistency and staleness checks, and feedback loops that improve generation quality over time. • Generate reference documentation from source (OpenAPI and related specs) and keep docs in sync with platform changes. • Lower the barrier for internal contributors to ship their own docs through the docs-as-code workflow. • Own release-notes and customer communications cadence with every platform release. • Maintain documentation style guide and ensure the function is not dependent on any one person.

• Own documentation as a system: the pipelines that build and publish it, AI-augmented workflows for drafts, review and publish process, and infrastructure for AI agents. • Take existing docs-as-code foundation and grow it into a docs-as-AI-agents capability. • Own the documentation site and its publishing as software: docs-as-code repo, CI/CD pipelines, automated link, structure, and quality checks. • Grow AI-augmented documentation workflows: AI-assisted drafting, summarization, consistency checks, and feedback loop improvements. • Structure content for AI systems consumption and maintain interfaces for agents. • Generate reference documentation from source and keep it aligned with code changes. • Lower barrier for internal contributors to ship their own docs through automation. • Own release-notes and customer communications cadence. • Maintain the documentation style guide and team runbook.

Role Description TetraScience is the scientific data and AI company. Our documentation is how customers, from bench scientists to platform engineers, learn to build on the platform, and increasingly it is how AI agents consume the platform too. We are looking for a Documentation Engineer to own documentation as a system: - Manage the pipelines that build and publish documentation. - Oversee AI-augmented workflows that generate drafts for human review and refinement. - Handle the review and publish process. - Ensure infrastructure makes documentation reliably consumable by AI agents. This is primarily a documentation systems role, not only a writer who uses tools. The differentiator is building and owning the systems that produce, validate, publish, and AI-enable our documentation. Strong writing and editorial judgment are still required, but the center of gravity is tooling and systems, and a large portion of the day-to-day is building. - Lead the growth of our existing docs-as-code foundation and AI-assisted documentation workflows into a docs-as-AI-agents capability. - Own editorial quality and the release-notes cadence while focusing on building leverage. - Own the documentation site and its publishing as software: the docs-as-code repo, CI/CD publishing pipelines, build performance, and automated checks. - Build and grow AI-augmented documentation workflows: AI-assisted drafting, summarization, classification, consistency and staleness checks, and a feedback loop for quality improvement. - Structure and transform content for AI systems to reliably chunk, index, and reason over it. - Generate reference documentation from source (OpenAPI and related specs) and maintain alignment with platform changes. - Lower the barrier for internal contributors to ship their own docs through the docs-as-code workflow and reduce repetitive work through automation. - Own the release-notes and customer-communications cadence with every platform release and run the SME review for accuracy and timeliness. - Own the documentation style guide, hold the review-and-publish gate, and keep the team runbook current. Qualifications - 5+ years owning documentation tooling, content engineering, or developer documentation for a developer-platform or enterprise B2B product. - Engineering ability in a scripting or web stack (e.g., Python, TypeScript, or JavaScript) and fluency with docs-as-code: Git, pull-request review, CI/CD, and a static-site or CMS publishing pipeline. - Hands-on experience building AI-augmented or LLM-backed workflows: integrating LLM APIs, AI-assisted authoring, and structuring content for AI consumption. - Ability to read and reason about a real codebase and API surface well enough to document it accurately and build tooling against it. - Strong editorial judgment: ability to clarify dense engineering changes for customer safety. - Bachelors or Masters degree in a technical field, or equivalent practical experience. Requirements - Experience making documentation consumable by AI agents (llms.txt, content negotiation, RAG pipelines, MCP servers). - Experience in BioPharma or scientific software, or in regulated and validated (GxP) environments. - Experience generating reference docs from OpenAPI or related specifications with two-way Git sync. - Developer-relations or developer-education exposure. Benefits - 100% employer-paid benefits for all eligible employees and immediate family members. - Unlimited paid time off (PTO). - 401K. - Flexible working arrangements - Remote work. - Company paid Life Insurance, LTD/STD. - A culture of continuous improvement where you can grow your career and get coaching.

Role Description Tetrascience is expanding rapidly and adding a Quality Engineer (QE) to one of our new teams focusing on use-cases for Scientific AI applications. The QE Engineer is expected to quickly grasp complex use-cases from early-stage applications, create comprehensive test plans and perform test automation. As a Senior QE Engineer, you will play a pivotal role in our product development lifecycle. Your responsibilities will include: - Take ownership of the QA process and product quality, emphasizing meticulous testing of scientific data applications and artifacts. - Review requirements and technical designs, providing timely and meaningful feedback. - Create, prioritize, plan, and execute test cases based on nuanced understanding of scientific application requirements and use-cases, ensuring coverage of all edge cases and meticulously tracking issues. - Utilize your quality engineering background to maintain strict quality processes in a fast-paced environment. - Collaborate effectively with scientists, data engineers, and application developers. - Be results-driven, proactively resolving blockers and evolving with requirements to drive tasks to resolution. - Continuously improve test coverage by reviewing customer issues and usage patterns. - Maintain curiosity about the underlying science and continuously learn and adapt to the application domain. - Design and implement robust, effective workflow-based automated tests using prior test automation experience within our AI-based Playwright framework. - Employ basic database experience to query and verify the integrity and correctness of scientific data. Qualifications - 8+ years as a Quality Engineer or Quality Assurance Engineer, with a focus on data testing. - Strong knowledge of software QA methodologies, tools and processes, particularly for data-intensive applications. - Proven expertise in designing comprehensive test plans, creating test cases, efficient reporting of test runs and defects for applications with evolving requirements. - Experience working in an Agile/Scrum development process. - Strong understanding of database systems and advanced SQL for querying, data verification, and testing data integrity. - Strong proficiency in AI-based test automation, particularly with Playwright, and experience testing data applications. - BS/MS degree in Computer Science, Engineering or a related subject. - Proactive and self-motivated, with the ability to thrive in a dynamic, fast-paced environment. Benefits - Competitive Salary and equity in a fast-growing company. - Supportive, team-oriented culture of continuous improvement. - Generous paid time off (PTO). - Flexible working arrangements - Remote work.

• Architect and evolve our cloud-native platform and services to support high-throughput, low-latency data processing patterns, customer-facing features, and design platform to meet scalability requirements. • Design scalable, distributed systems powering complex capabilities such as authentication & authorization, data lifecycle management, metadata management, operational intelligence, and real-time event processing. • Evolve the authorization service toward modern identity standards and customer-configurable, fine-grained access models that scale without a release for every new role including authorization for non-human identities (service-to-service, AI agents, MCP-based tooling). • Built systems that capture and enforce structured metadata at ingest and serve it through clean service contracts; understands where platform metadata plumbing ends and the semantic/ontology layer begins, and collaborates well across that boundary. • Build governance primitives for a regulated environment — compliance-grade audit trail, dataset-level access controls, and approval / eSignature workflows. • Collaborate with engineering and product teams to deliver infrastructure that supports new services, customer-facing applications, and high-volume data processing workloads. • Build and maintain infrastructure-as-code (e.g., CloudFormation, AWS CDK) to automate, standardize, and secure deployments to support online upgrades and on-demand infrastructure allocation. • Enhance observability and monitoring to ensure reliability, cost efficiency, and rapid incident response. • Champion best practices in distributed systems design, scalability, and performance optimization, and share architectural insights through design reviews and technical documentation.

Role Description Own the cloud infrastructure, CI/CD systems, and deployment automation for TetraScience’s multi-tenant SaaS platform serving global biopharma customers. This is a hands-on technical lead role. You will lead through technical depth and influence across teams. Strong architecture and implementation skills are important for success in this role. You will evolve our cloud architecture, build substantial parts of it in Python, CloudFormation and Terraform. You will architect and build deployment pipelines to AWS and Databricks, and drive the engineering practices that determine how fast and safely we ship software. Qualifications - 7+ years in DevOps, Cloud Engineering, or Platform Engineering roles, with at least 2 years in a senior or lead capacity - Deep, daily-driver coding experience: programmatically managing infrastructure through Python, APIs and IaC tools is second nature to you. The web console is an afterthought. - Strong production AWS experience: compute (EKS, ECS, EC2), networking (VPC, Transit Gateway, ALB/NLB, Route53), storage (S3, EBS, EFS), security (IAM, KMS, Security Hub, GuardDuty) - Designed and built CI/CD pipeline infrastructure (not just consumed existing pipelines). GitHub Actions, GitLab CI, or Jenkins at scale. - Container orchestration: ECS, Docker, Kubernetes (EKS preferred), service mesh concepts - Scripting and automation: Python or Go. Bash only is not enough - Git-based workflows, branch strategies, and pull-request-driven infrastructure changes - Experience designing and operating resilient and scalable cloud solutions - Experience operating in a regulated or compliance-sensitive environment (GxP, SOC2, HIPAA, FedRAMP, or similar) Requirements - Deep, hands-on AWS experience: Serverless Architecture, EKS/ECS, VPC/networking, IAM, KMS, CloudWatch, Lambda, S3, EC2, Kinesis, Athena, Glue, CloudTrail, CostExplorer. - Understanding of Well-Architected Framework principles and application in daily work. - Databricks experience is strongly preferred. - Embed security into the product and pipelines: container image scanning, SAST/DAST integration, secrets management, least-privilege IAM, and compliance-as-code. - Work in a GxP-regulated environment where auditability and traceability of deployments are non-negotiable. - Production monitoring, alerting, log aggregation, and incident response infrastructure. - Support for developer teams with a blameless postmortem culture. Benefits - Competitive compensation with equity - Unlimited PTO - Flexible remote-first work arrangements - Company-paid Life Insurance, LTD/STD - 401(k)

Scientific Solutions Partner - Copenhagen, Denmark Hybrid Solutions Architect Full time Copenhagen, Capital Region of Denmark, Denmark What You’ll Do Scientific & Technical Engagement ● Lead technical discovery: understand the customer’s current lab data landscape — instruments, data formats, informatics stack, and data science ambitions ● Design and present compelling solution architectures aligned to the customer’s specific scientific use cases (e.g., ADMET assays, FPLC/UPLC chromatography, bioassay data harmonization, AI training datasets) as well as understanding their core data management pain points and goals. ● Always be leading with demo’s of actual software aligned to the customers main value levers. ● Own and drive proof-of-concept and proof-of-value engagements, partnering with TetraScience scientific data architects to deliver credible, high-quality demonstrations of the Tetra Scientific Data Foundry’s capabilities ● Own RFP technical responses end-to-end, synthesizing platform capabilities, scientific use cases, and customer-specific requirements into compelling, accurate submissions ● Articulate the medallion data architecture in scientific and business terms: how bronze (raw scientific data), silver (harmonized Tetra Data), and gold (analysis-ready datasets) each create value, and how TetraScience’s AI-native layer accelerates scientific outcomes ● Stay current on the scientific and informatics landscape — relevant assay workflows, instrument vendors, SDMS/ELN/LIMS/analytical software integrations, and AI/ML use cases in drug discovery and development   Commercial Ownership ● Prospect, qualify, and build territory pipeline in alignment with the TetraScience go-to-market strategy ● Relentlessly identify and close expansion opportunities across new labs, instruments, geographies, sites, and use cases within existing accounts ● Manage the full sales cycle from discovery through contracting, using modern sales methodologies (MEDDIC, MEDDPIC, Force Management, or similar) ● Maintain a rigorous, accurate pipeline with consistent forecasting and visibility to leadership ● Build and expand relationships across the customer organization, from individual contributors to executive sponsors ● Identify and close expansion opportunities across new labs, instruments, geographies, sites, and use cases within existing accounts ● Partner with the Delivery Manager to ensure smooth handoff from sales to delivery, maintaining continuity of scientific context   Market & Thought Leadership ● Represent TetraScience at industry conferences, seminars, and customer events as a scientifically credible voice ● Contribute customer and market insights back to product, marketing, and science teams to inform roadmap and messaging ● Help develop compelling content — case studies, solution briefs, demo narratives — that advances the category Requirements   What You Bring ● Advanced degree in a life science, chemistry, or engineering discipline preferred MS or PhD); equivalent practical experience considered ● 7+ years of combined scientific, technical, and commercial experience in life sciences software, laboratory informatics, scientific data infrastructure, or adjacent domains ● Direct experience in pharma, biotech, or CRO/CDMO environments — either as a scientist, scientific software professional, or sales/solutions professional serving these customers ● Demonstrated ability to lead technical sales cycles in enterprise SaaS or scientific software, including POC design and execution and RFP ownership ● Deep familiarity with laboratory workflows and data: you understand what it means when a customer has 50 instruments generating unstructured data that no one can analyze ● Fluency with scientific data concepts: file formats, instrument connectivity, data harmonization, and the path from raw data to AI-ready datasets ● Experience with modern sales methodologies (MEDDIC, MEDDPIC, Force Management, or similar) ● Strong executive presence — equally compelling in a whiteboard architecture session and a C-suite business case conversation ● Proficiency with CRM and digital sales tools (Salesforce, LinkedIn Sales Navigator, ZoomInfo, SalesLoft, or equivalent) ● Ability to travel (approximately 25%) to client sites within assigned region Benefits   - Competitive Salary and equity in a fast-growing company. - Supportive, team-oriented culture of continuous improvement. - Generous paid time off (PTO). - Flexible working arrangements - Remote work.