TetraScience

Compliance

• Serve as a senior US compliance authority for TetraScience products, for FDA-aligned regulatory interpretation (21 CFR Part 11, Computer Software Assurance / CSA, predicate rules) and US customer expectations.
• Lead customer-facing regulatory conversations as a trusted, named counterpart to pharma and biotech Quality and Validation leadership — providing direct guidance, working-session coaching, and written attestations on both platform-side qualification and customer-side production validation.
• Guide customers through last-mile validation of their intended use of TetraScience — including validation scoping, plan templates, risk assessments, traceability, and CSA-aligned testing approaches — so customer teams can validate scientific workflows on TetraScience faster and with higher quality.
• Own the platform quality and validation narrative for TetraScience itself — how the platform, components, AI Services, and connected agents are qualified, change-controlled, and evidenced — and translate that narrative into customer-consumable artifacts (qualification summaries, GxP impact assessments, release impact letters, IQ reports).
• Lead customer audits and supplier assessments hosted out of the US, including pre-audit readiness, evidence preparation, audit hosting, and findings remediation, for top-tier pharma and biotech accounts.
• Own the GxP Package strategy and roadmap for the US market — including documentation, validation templates, controlled environment attestations, and last-mile validation enablement — to reduce burden on pharma compliance and QA teams.
• Improve the regulatory framework for AI-enabled product capabilities: GAMP 5 + GAMP AI categorization, model validation expectations (e.g., Life Cycle Software Assurance, vision and language models), and customer-facing AI impact assessment artifacts.
• Own and continuously improve the Quality Management System in Qualio, including SOP lifecycle, ensuring it remains audit-ready and aligned with evolving US regulatory expectations.
• Partner with Product and Engineering on platform-level compliance decisions — audit trail design, electronic signatures (21 CFR 11.50), data residency, multi-tenant vs. single-tenant validated environments — acting as the regulatory voice in architectural trade-offs.
• Maintain compliance readiness for ISO 9001 and other certifications, including annual surveillance audits, recertifications, and continuous evidence collection.
• Independently lead cross-functional remediation when audit findings, customer escalations, or regulatory gaps surface — without requiring day-to-day direction.
• Train and enable customer-facing teams (Sales, Solutions Architecture, Implementation, Customer Success) on platform-vs-production validation framing, GxP Package usage, and the boundaries of TetraScience's qualification versus customer last-mile validation.
• Contribute to Sales, Implementation, and Customer Success engagements as the US regulatory subject matter expert, including RFP/RFI responses, compliance matrices, and executive-level customer compliance discussions.

Senior Compliance Manager

Data Engineer

• You will be a critical team member in a unique partnership to industrialize Scientific AI.
• Engage directly with customers onsite a couple of days per week in the Indianapolis area, building strong relationships, deeply understanding their scientific data challenges and requirements, and accelerating solutions.
• Design and implement extensible, reusable data models that efficiently capture and organize scientific data for scientific use cases, ensuring scalability and future adaptability.
• Translate scientific data workflows into robust solutions leveraging the Tetra Data Platform.
• Own, scope, prototype, and implement solutions including:
• - Data model design (tabular & JSON)
• - Python-based parser development.
• - Lab software (e.g., ELN/LIMS) integration via APIs.
• - Data visualization and app development in Python (using app frameworks like Streamlit and plotting tools like holoviews and Plotly)
• Collaborate with Scientific Business Analysts (SBAs), customer scientists and applied AI engineers to develop and deploy models (ML, AI, mechanistic, statistical, hybrid).
• Programmatically interrogating proprietary instrument output files.
• Dynamically iterate with scientific end users and technical stakeholders to rapidly drive solution development and adoption through regular demos and meetings.
• Proactively communicate implementation progress and deliver demos to customer stakeholders.
• Collaborate with the product team to build and prioritize our roadmap by understanding customers’ pain points within and outside Tetra Data Platform.
• Rapidly learn new technologies (e.g., new AWS services or scientific analysis applications) to develop and troubleshoot use cases.
• Must be able to travel to client sites in St. Louis, Indianapolis, Chicago regions.

Scientific Data Architect

• Engage directly with customers onsite up to 3-4 days per week in the Waltham Region, building strong relationships, deeply understanding their scientific data challenges and requirements, and accelerating solutions.
• Design and implement extensible, reusable data models that efficiently capture and organize scientific data for scientific use cases, ensuring scalability and future adaptability.
• Translate scientific data workflows into robust solutions leveraging the Tetra Data Platform.
• Own, scope, prototype, and implement solutions including:
• - Data model design (tabular & JSON)
• - Python-based parser development.
• - Lab software (e.g., ELN/LIMS) integration via APIs.
• - Data visualization and app development in Python (using app frameworks like Streamlit and plotting tools like holoviews and Plotly)
• Collaborate with Scientific Business Analysts (SBAs), customer scientists, and applied AI engineers to develop and deploy models (ML, AI, mechanistic, statistical, hybrid)
• Programmatically interrogate proprietary instrument output files.
• Dynamically iterate with scientific end users and technical stakeholders to rapidly drive solution development and adoption through regular demos and meetings.
• Proactively communicate implementation progress and deliver demos to customer stakeholders.
• Collaborate with the product team to build and prioritize our roadmap by understanding customers’ pain points within and outside Tetra Data Platform.
• Rapidly learn new technologies (e.g., new AWS services or scientific analysis applications) to develop and troubleshoot use cases

Manager

• Own end-to-end program delivery for a portfolio of enterprise customers, including implementation of instrument connectivity, Tetra OS data pipeline configuration (bronze/silver/gold), and scientific use case enablement & adoption.
• Navigate the full complexity of enterprise pharma delivery environments: SSO provisioning, IT security reviews, validation hurdles, procurement workflows, and change control processes — clearing blockers proactively so that go-live happens ahead of schedule, not behind it
• Hold the delivery pace even when the customer isn't pressing. Look around corners for timeline drag and scope creep, and resolve them through direct action or by identifying & moving the customer stakeholders who can unblock.
• Lead project kick-off, milestone tracking, resource planning, scope management, and project closure across multiple concurrent workstreams
• Manage and document change requests, ensuring scope changes are assessed, approved, and communicated with minimal disruption to timelines
• Maintain rigorous delivery governance: roles, responsibilities, decision rights, and escalation paths
• Coordinate internal teams, external vendors, customer stakeholders and management on both sides to ensure effective scientific outcomes..
• Serve as the primary operational point of contact for customer delivery stakeholders (Lab IT, informatics, project management, and scientific leads)
• Navigate customer political dynamics with fluency — building trust across scientific, IT, and procurement stakeholders simultaneously
• Run structured customer update meetings, steering committees, and executive delivery reviews
• Proactively manage risks and customer expectations; surface issues early and drive to resolution before they become escalations
• Ensure successful customer handoff from implementation to steady-state, with clear documentation and success criteria met
• Coordinate cross-functional TetraScience resources — scientific data engineers, technical architects, product — to meet delivery commitments
• Escalate technical issues to the Technical Delivery Director with clear context and business impact framing
• Contribute to continuous improvement of TetraScience’s delivery methodology, templates, and tooling

Customer Delivery Manager

Director

• Own end-to-end program delivery for a portfolio of enterprise customers, including implementation of instrument connectivity, Tetra OS data pipeline configuration (bronze/silver/gold), and scientific use case enablement & adoption.
• Navigate the full complexity of enterprise pharma delivery environments: SSO provisioning, IT security reviews, validation hurdles, procurement workflows, and change control processes — clearing blockers proactively so that go-live happens ahead of schedule, not behind it
• Hold the delivery pace even when the customer isn't pressing. Look around corners for timeline drag and scope creep, and resolve them through direct action or by identifying & moving the customer stakeholders who can unblock.
• Lead project kick-off, milestone tracking, resource planning, scope management, and project closure across multiple concurrent workstreams
• Manage and document change requests, ensuring scope changes are assessed, approved, and communicated with minimal disruption to timelines
• Maintain rigorous delivery governance: roles, responsibilities, decision rights, and escalation paths
• Coordinate internal teams, external vendors, customer stakeholders and management on both sides to ensure effective scientific outcomes.
• Serve as the primary operational point of contact for customer delivery stakeholders (Lab IT, informatics, project management, and scientific leads)
• Navigate customer political dynamics with fluency — building trust across scientific, IT, and procurement stakeholders simultaneously
• Run structured customer update meetings, steering committees, and executive delivery reviews
• Proactively manage risks and customer expectations; surface issues early and drive to resolution before they become escalations
• Ensure successful customer handoff from implementation to steady-state, with clear documentation and success criteria met
• Partner with Scientific & IT leaders to build and surface the customer's value realization story throughout the engagement: quantify scientific outcomes, translate them into ROI language senior budget owners will accept, and make that story visible to decision makers well before renewal windows open.
• Actively develop expansion pipelines (additional instruments, labs, use cases, sites, adjacent scientific workflows). Shape the commercial case jointly with the Scientific Solutions Partner and drive qualified opportunities into the account plan.
• Feed delivery intelligence into account strategy: stakeholder dynamics, unmet needs, political landscape, competitive signals. Advise with the SSP on timing and sequencing of expansion plays.
• Coordinate cross-functional TetraScience resources — scientific data engineers, technical architects, product — to meet delivery commitments
• Escalate technical issues to the Technical Delivery Director with clear context and business impact framing
• Contribute to continuous improvement of TetraScience’s delivery methodology, templates, and tooling

Customer Delivery Director

Full-stack Engineer

• Design, implement, and operate core systems for TetraScience's artifact and registry platform, spending substantial day-to-day time writing production code across services, APIs, SDKs, CLIs, data models, and platform workflows.
• Define durable technical boundaries between existing package/artifact infrastructure and Tetra-specific registry, contract, governance, lineage, and developer experience systems.
• Design APIs, SDK/CLI workflows, registry models, and developer workflows for authoring, validating, publishing, versioning, promoting, consuming, and deprecating reusable software artifacts.
• Establish strong semantics for versioning, compatibility, immutability, dependency metadata, governance tiers, environment promotion, and supply-chain integrity.
• Build guardrails that make AI agents and human developers safe, productive first-class builders, including validation, provenance, policy enforcement, observability, and clear failure modes.
• Create architecture that supports scientific auditability, lineage, and regulated workflows without making early builder workflows unnecessarily heavy.
• Lead critical technical paths from design through implementation, production rollout, observability, and operational ownership, partnering with Product, Engineering, and field teams to turn platform strategy into staged delivery.
• Identify where mature open-source or commercial systems should be reused, where TetraScience needs an opinionated product layer, and how the architecture should evolve as the system matures.
• Review code, write design documents, mentor engineers, and raise the technical bar for platform design, implementation quality, documentation, and operations.

Software Engineering Technical Lead – Platform, Primitives & Registry

Architect

• Architect the Exchange Layer: Design and own the Common Data Models (CDMs) that serve as the universal language for scientific data across our customer base. Move the platform from bespoke, one-off mappings to a standardized "exchange layer" that ensures interoperability.
• Empower Forward Deployed Engineering: Create the data contracts and standardized definitions that FDEs rely on. Your models will be the toolkit that allows them to deploy faster and with higher confidence, knowing they are building on a stable, consistent semantic foundation.
• Standardization vs. Flexibility: Strike the strategic balance between rigid global standards (for cross-customer exchange) and local flexibility. Define the core "immutable" aspects of the model versus where extension is permitted.
• Translate high-level business goals (e.g., "accelerate time-to-insight for biologics") into concrete data modeling strategies. Ensure our semantic roadmap directly supports the scientific questions our customers—and our internal teams—need to answer.
• Roll up your sleeves to design and implement complex ontologies and taxonomies. Model intricate scientific relationships (e.g., linking a "Cell Line" in an ELN to "Flow Cytometry Results") with precision.
• Work directly with Engineering to architect the software systems that consume these models. Ensure that the "perfect" ontology does not break query performance or system scalability.
• Establish the "rules of the road" for data quality and consistency. Define how data contracts are versioned, enforced, and evolved, ensuring that downstream consumers (AI teams, FDEs, Scientists) can trust the data structure.
• Partner with Scientific Business Analysts to decode the complexity of biopharma R&D. Turn ambiguous scientific requirements into rigorous, machine-readable data structures.
• Architect models that ensure our data is FAIR (Findable, Accessible, Interoperable, Reusable) and ready for downstream AI/ML applications.

Data & Semantic Model Architect

DevOps Engineer

• - Design, build, and maintain all cloud infrastructure using Terraform (primary) across AWS and Azure.
• - Own the build, test, and deployment pipeline infrastructure end to end.
• - Deep, hands-on AWS work: EKS/ECS, VPC architecture, IAM, KMS, CloudWatch, Lambda, S3, networking.
• - Embed security into the pipeline: container image scanning, SAST/DAST integration, secrets management, least-privilege IAM, compliance-as-code.
• - Partner with engineering teams to reduce cycle time from commit to production.
• - Production monitoring, alerting, log aggregation, and incident response infrastructure.

Technology Lead, DevOps Engineering

• You will be leading the Scientific Data Engineering (SDE) Team and helping build Tetra Data and productizable solutions, which is the foundation of the Data Engineering layer.
• We are looking for a data engineer who is experienced, hands-on, and can also provide mentorship to junior team members.
• As a Senior Scientific Data Engineer, you should be comfortable leading internal design sessions and architecting solutions.
• You will work directly with Product Managers and Solution Architects to gather business and data design objectives, resulting in production-based solutions.
• You will be a team-focused leader, have excellent data engineering skills, supervise and collaborate on project executions, and have a high commitment to customer success by delivering mission-critical implementations.
• Work with Product Managers and Solution Architects to understand business requirements, gather insight into potential positive outcomes, recommend potential outcomes, and build a solution based on consensus.
• Take ownership of building data models, prototypes, and integration solutions that drive customer success.
• Use AI agents to build comprehensive data schemas and parsers for pre-clinical data (main data sources: R&D lab instruments, manufacturing, CRO, CDMO, ELN, LIMS) with various data formats: .xlsx, .pdf, .txt, .raw, .fid, many other vendor binaries.
• Extract reusable schema components and parsing functions, and productize them into Python libraries.
• Build high-quality data pipelines with full unit test and integration test coverage to produce high-fidelity data.
• Build data applications, reports, and dashboards using React, Streamlit, Jupyter notebook, etc.
• Work closely with product managers, project managers, business analysts, data architects, and ML engineers to deliver best-in-class data products.
• Drive value for the customers - verify the solution fulfills their requirements and provides value.
• Quality gatekeeper: design with quality backed by unit tests, integration tests, and utility functions.
• Lead team-wide process/technology improvements on product quality and developer experience.
• Rally the team to finish Agile Sprint commitments. Actively surfacing team inefficiencies and striving to resolve them.
• Driven by results. Have the pragmatic urgency to resolve blockers, unclear requirements, and make things happen.
• Provide mentorship to junior SDEs and show leadership in every front.

Senior Scientific Data Engineer

• Own end-to-end program delivery for a portfolio of enterprise customers, including implementation of instrument connectivity, Tetra OS data pipeline configuration (bronze/silver/gold), and scientific use case enablement & adoption.
• Navigate the full complexity of enterprise pharma delivery environments: SSO provisioning, IT security reviews, validation hurdles, procurement workflows, and change control processes — clearing blockers proactively so that go-live happens ahead of schedule, not behind it
• Hold the delivery pace even when the customer isn't pressing. Look around corners for timeline drag and scope creep, and resolve them through direct action or by identifying & moving the customer stakeholders who can unblock.
• Lead project kick-off, milestone tracking, resource planning, scope management, and project closure across multiple concurrent workstreams
• Manage and document change requests, ensuring scope changes are assessed, approved, and communicated with minimal disruption to timelines
• Maintain rigorous delivery governance: roles, responsibilities, decision rights, and escalation paths
• Coordinate internal teams, external vendors, customer stakeholders and management on both sides to ensure effective scientific outcomes.
• Serve as the primary operational point of contact for customer delivery stakeholders (Lab IT, informatics, project management, and scientific leads)
• Navigate customer political dynamics with fluency — building trust across scientific, IT, and procurement stakeholders simultaneously
• Run structured customer update meetings, steering committees, and executive delivery reviews
• Proactively manage risks and customer expectations; surface issues early and drive to resolution before they become escalations
• Ensure successful customer handoff from implementation to steady-state, with clear documentation and success criteria met
• Actively develop expansion pipelines (additional instruments, labs, use cases, sites, adjacent scientific workflows). Shape the commercial case jointly with the Scientific Solutions Partner and drive qualified opportunities into the account plan.
• Feed delivery intelligence into account strategy: stakeholder dynamics, unmet needs, political landscape, competitive signals. Advise with the SSP on timing and sequencing of expansion plays.
• Coordinate cross-functional TetraScience resources — scientific data engineers, technical architects, product — to meet delivery commitments
• Escalate technical issues to the Technical Delivery Director with clear context and business impact framing
• Contribute to continuous improvement of TetraScience’s delivery methodology, templates, and tooling

• Own end-to-end program delivery for a portfolio of enterprise customers, including implementation of instrument connectivity, Tetra OS data pipeline configuration (bronze/silver/gold), and scientific use case enablement & adoption.
• Navigate the full complexity of enterprise pharma delivery environments: SSO provisioning, IT security reviews, validation hurdles, procurement workflows, and change control processes — clearing blockers proactively so that go-live happens ahead of schedule, not behind it
• Hold the delivery pace even when the customer isn't pressing. Look around corners for timeline drag and scope creep, and resolve them through direct action or by identifying & moving the customer stakeholders who can unblock.
• Lead project kick-off, milestone tracking, resource planning, scope management, and project closure across multiple concurrent workstreams
• Manage and document change requests, ensuring scope changes are assessed, approved, and communicated with minimal disruption to timelines
• Maintain rigorous delivery governance: roles, responsibilities, decision rights, and escalation paths
• Coordinate internal teams, external vendors, customer stakeholders and management on both sides to ensure effective scientific outcomes.
• Serve as the primary operational point of contact for customer delivery stakeholders (Lab IT, informatics, project management, and scientific leads)
• Navigate customer political dynamics with fluency — building trust across scientific, IT, and procurement stakeholders simultaneously
• Run structured customer update meetings, steering committees, and executive delivery reviews
• Proactively manage risks and customer expectations; surface issues early and drive to resolution before they become escalations
• Ensure successful customer handoff from implementation to steady-state, with clear documentation and success criteria met
• Coordinate cross-functional TetraScience resources — scientific data engineers, technical architects, product — to meet delivery commitments
• Escalate technical issues to the Technical Delivery Director with clear context and business impact framing
• Contribute to continuous improvement of TetraScience’s delivery methodology, templates, and tooling

Platform Engineer

• 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).

Senior Software Platform Engineer

• Architect a full-stack Search Platform across all layers of indexing and scoring, query understanding, rewriting and federation, and extensible search experiences.
• Continuously improve search quality through evaluation metrics such as precision@K, recall@K, MRR, and relevance testing with real scientific use cases.
• Engineer sophisticated hybrid search pipelines that blend sparse (keyword), structured (metadata), and dense (vector) retrieval. You will go beyond out-of-the-box OpenSearch to design custom ranking logic, reciprocal rank fusion, and relevance tuning that surfaces the exact "needle in the haystack" for drug discovery.
• Lead by example and write code, review designs, and set the standard for engineering quality on the Search Platform team. Mentor engineers and help grow the team's search and distributed systems expertise.
• Contribute to architectural decisions, technical strategy, and platform-wide improvements to accelerate scientific insight generation.
• Own and operate the Search Platform infrastructure, ensuring high availability, scalability, performance, and observability across indexing, embedding generation, and query execution.
• Develop and maintain backend services and APIs in Python and TypeScript that power search capabilities for scientists, data engineers, and AI applications.
• Ensure security, compliance, and tenant isolation as part of operating search services in enterprise bio-pharma environments.
• Collaborate with Applied AI Scientists to integrate embeddings, transformer models, and chemical fingerprints into production search workflows.
• Architect and implement scientific entity resolution and knowledge graph pipelines to transform raw text into interconnected knowledge. You will design systems that extract and link chemical and biological entities (NER/NED) from unstructured documents, enabling the search engine to "understand" relationships between compounds, targets, and assays.

Senior Compliance Manager

Scientific Data Architect

Scientific Data Architect

Customer Delivery Manager

Customer Delivery Director

Software Engineering Technical Lead – Platform, Primitives & Registry

Data & Semantic Model Architect

Technology Lead, DevOps Engineering

Senior Scientific Data Engineer

Customer Delivery Director

Customer Delivery Manager

Senior Software Platform Engineer

Lead Software Engineer – Search Platform