TetraScience

Architect and maintain scalable distributed applications using C#, .NET, and TypeScript with AWS microservices and CI/CD pipelines. | Strong proficiency in C#/.NET, TypeScript/React, AWS cloud services, microservices architecture, production debugging, automated testing, and CI/CD pipelines. | ABOUT TETRASCIENCE TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft. In connection with your candidacy, you will be asked to carefully review “The Tetra Way,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you. The Role We are seeking a highly skilled Senior .NET Engineer to join our dynamic team. The ideal candidate will have extensive experience in designing and developing high-performance, scalable applications using C#, the .NET Framework, and TypeScript. The role involves implementing automated testing and leveraging GitHub Actions for CI/CD pipelines. The candidate should also be proficient in production debugging and possess excellent communication skills. Knowledge and experience with AWS cloud services are also essential. What You Will Do High-Performance, Distributed, and Scalable Application Design: Architect, design, and maintain distributed applications, ensuring high performance, scalability, and security. Full-Stack Development: Develop backend services (primarily C#/.NET and TypeScript) and cloud APIs, as well as modern, responsive front-end applications using TypeScript/React. Microservices Architecture: Design and implement loosely coupled, independently deployable services using AWS services such as DynamoDB, RDS, SQS, Lambda, API Gateway, and others. Automated Testing: Create and maintain automated unit, integration, contract, and end-to-end tests across microservices and UI layers. CI/CD Pipelines: Use GitHub Actions to implement and maintain CI/CD pipelines for both backend services and front-end applications. Production Debugging & Optimization: Diagnose and resolve production issues in distributed systems, including service-to-service communication, CPU/memory/network bottlenecks, and AWS service performance. Observability & Operational Excellence: Instrument services using OpenTelemetry (or equivalent) to enable earlier fault detection, clearer alerting, and stronger operational visibility. Contribute to SLO definition and MTTR reduction efforts across the platform. Collaboration & Communication: Work closely with product managers, tech leads, and other engineers to deliver reliable, maintainable, and scalable solutions. Communicate technical decisions clearly to both technical and non-technical stakeholders. What You Will Bring Required Skills Strong proficiency in backend service development using C#/.NET. Strong proficiency in TypeScript and React for front-end UI. Experience building and operating software in both on-premises/customer-hosted environments and cloud-native multi-tenant environments, with an understanding of how debugging, deployment, and scaling differ between the two. Hands-on experience with AWS DynamoDB, RDS, SQS (or an equivalent cloud provider) in production environments. Experience with microservices patterns (service discovery, API gateway, messaging/queueing, data partitioning). Experience with automated testing at multiple levels. Strong Git skills and hands-on experience with GitHub Actions for CI/CD. Strong troubleshooting skills for distributed systems in production. Solid understanding of cloud-native architecture and AWS best practices. Familiarity with observability tooling and practices (OpenTelemetry, structured logging, distributed tracing, metrics-based alerting) to support proactive issue detection. Desirable Skills Familiarity with containerization (Docker) and experience defining AWS infrastructure using CloudFormation (or AWS CDK) to support predictable and repeatable environments. Experience with performance tuning and designing scalable solutions. Experience with, or exposure to, scientific instrument software / Chromatography Data Systems (CDS) e.g., Waters Empower, Thermo Chromeleon, Cytiva UNICORN, Agilent OpenLab, along with knowledge of instrument integration pattern and practices is a strong plus. Soft Skills Needed: Excellent verbal and written communication. Strong collaboration skills in cross-functional teams. Analytical mindset with high attention to detail. Why TetraScience Mission-driven: your infrastructure directly enables scientific drug development processes that save and extend lives. Builder culture: everyone ships — engineers, managers, and leadership. No passengers. Technically ambitious: we are rebuilding how science-grade data infrastructure works, not deploying off-the-shelf solutions. AI-first: we apply AI across every layer of the platform today, not as a future roadmap item. Competitive compensation, meaningful equity, and strong 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 No visa sponsorship is available for this position The salary range for this position is $170,000-$220,000 USD. The salary range posted reflects our target baseline for this role. Final compensation is determined by a thorough evaluation of factors including the candidate’s specific experience, localized market data, and internal team equity.

Architect and maintain scalable distributed applications with CI/CD and observability. | Strong proficiency in C#/.NET, TypeScript, React, AWS, microservices, automated testing, and production debugging. | ABOUT TETRASCIENCE TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft. The Role We are seeking a highly skilled Senior .NET Engineer to join our dynamic team. The ideal candidate will have extensive experience in designing and developing high-performance, scalable applications using C#, the .NET Framework, and TypeScript. The role involves implementing automated testing and leveraging GitHub Actions for CI/CD pipelines. The candidate should also be proficient in production debugging and possess excellent communication skills. Knowledge and experience with AWS cloud services are also essential. What You Will Do High-Performance, Distributed, and Scalable Application Design: Architect, design, and maintain distributed applications, ensuring high performance, scalability, and security. Full-Stack Development: Develop backend services (primarily C#/.NET and TypeScript) and cloud APIs, as well as modern, responsive front-end applications using TypeScript/React. Microservices Architecture: Design and implement loosely coupled, independently deployable services using AWS services such as DynamoDB, RDS, SQS, Lambda, API Gateway, and others. Automated Testing: Create and maintain automated unit, integration, contract, and end-to-end tests across microservices and UI layers. CI/CD Pipelines: Use GitHub Actions to implement and maintain CI/CD pipelines for both backend services and front-end applications. Production Debugging & Optimization: Diagnose and resolve production issues in distributed systems, including service-to-service communication, CPU/memory/network bottlenecks, and AWS service performance. Observability & Operational Excellence: Instrument services using OpenTelemetry (or equivalent) to enable earlier fault detection, clearer alerting, and stronger operational visibility. Contribute to SLO definition and MTTR reduction efforts across the platform. Collaboration & Communication: Work closely with product managers, tech leads, and other engineers to deliver reliable, maintainable, and scalable solutions. Communicate technical decisions clearly to both technical and non-technical stakeholders. What You Will Bring Required Skills Strong proficiency in backend service development using C#/.NET. Strong proficiency in TypeScript and React for front-end UI. Experience building and operating software in both on-premises/customer-hosted environments and cloud-native multi-tenant environments, with an understanding of how debugging, deployment, and scaling differ between the two. Hands-on experience with AWS DynamoDB, RDS, SQS (or an equivalent cloud provider) in production environments. Experience with microservices patterns (service discovery, API gateway, messaging/queueing, data partitioning). Experience with automated testing at multiple levels. Strong Git skills and hands-on experience with GitHub Actions for CI/CD. Strong troubleshooting skills for distributed systems in production. Solid understanding of cloud-native architecture and AWS best practices. Familiarity with observability tooling and practices (OpenTelemetry, structured logging, distributed tracing, metrics-based alerting) to support proactive issue detection. Desirable Skills Familiarity with containerization (Docker) and experience defining AWS infrastructure using CloudFormation (or AWS CDK) to support predictable and repeatable environments. Experience with performance tuning and designing scalable solutions. Experience with, or exposure to, scientific instrument software / Chromatography Data Systems (CDS) e.g., Waters Empower, Thermo Chromeleon, Cytiva UNICORN, Agilent OpenLab, along with knowledge of instrument integration pattern and practices is a strong plus. Soft Skills Needed: Excellent verbal and written communication. Strong collaboration skills in cross-functional teams. Analytical mindset with high attention to detail. Why TetraScience Mission-driven: your infrastructure directly enables scientific drug development processes that save and extend lives. Builder culture: everyone ships — engineers, managers, and leadership. No passengers. Technically ambitious: we are rebuilding how science-grade data infrastructure works, not deploying off-the-shelf solutions. AI-first: we apply AI across every layer of the platform today, not as a future roadmap item. Competitive compensation, meaningful equity, and strong 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 No visa sponsorship is available for this position The salary range for this position is $170,000-$220,000 USD. The salary range posted reflects our target baseline for this role. Final compensation is determined by a thorough evaluation of factors including the candidate’s specific experience, localized market data, and internal team equity.

Design and maintain cloud-native platforms and MLOps pipelines to support scalable AI and data workloads. | Requires 7+ years in software and infrastructure engineering with expert Python and TypeScript and production experience in Databricks MLFlow, AWS, and containerization. | About TetraScience TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft. In connection with your candidacy, you will be asked to carefully review “The Tetra Way,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you. What You will Do 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). 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 We are not currently providing visa sponsorship for this position.

Lead architecture and development of a full-stack search platform integrating advanced search and AI models. | Over 10 years backend/platform engineering with expertise in search technologies, Python, TypeScript, semantic retrieval, and distributed systems. | About TetraScience TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft. In connection with your candidacy, you will be asked to carefully review “The Tetra Way,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you. The Role We're building a search platform that helps scientists find answers across billions of data points from chemical structures and assay results to unstructured lab documents and instrument data. We're looking for a Lead/Principal Platform Engineer to lead that effort. You'll own the full search stack: indexing and scoring, query understanding and rewriting, retrieval pipelines, and the infrastructure underneath it all. You should be able to fluently apply the state-of-the-art in classical search, custom analyzers, index design alongside newer methods for semantic and hybrid retrieval. You'll go well beyond out-of-the-box OpenSearch to build custom ranking logic, relevance tuning, and scoring models that surface the right result from massive, heterogeneous scientific datasets. This is a hands-on technical leadership role. As the technical leader of the Search Platform team, you'll write code, architect systems, mentor engineers, and shape the roadmap for search capabilities and platform evolution. You'll often operate in ambiguous territory translating loosely defined scientific workflows into well-architected search systems where the "right answer" isn't always obvious and requirements evolve as scientists discover new ways to use the platform. You'll collaborate daily with Applied AI Scientists, platform engineers, and product teams to deliver high-performance search services that drive discovery, analysis, and decision-making across the bio-pharma R&D lifecycle. The domain is bio-pharma R&D, and the data types are fascinating molecular structures (SMILES), experimental datasets, knowledge graphs linking compounds to targets and assays. You don't need to know cheminformatics today, but you should be excited to apply deep search expertise to novel and complex data types. If you've spent your career building scalable search systems and want to do it at the intersection of AI and scientific discovery, we'd love to talk. What You will Do 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. 10+ years of backend or platform engineering experience building distributed, production grade systems. Hands-on experience with search technologies such as Elasticsearch/OpenSearch, Lucene, or vector databases not just deployment, but custom configuration, relevance tuning, and performance optimization at scale. Strong understanding of semantic and hybrid retrieval: embeddings, transformer models, vector similarity, ranking logic, relevance tuning, and how to blend them with classical keyword search. Expert-level coding skills in TypeScript and Python building robust APIs and backend services. Proven ability to build and operate search infrastructure on cloud platforms (AWS preferred), including containerization, CI/CD, observability, and capacity planning. Familiarity with scientific or unstructured data processing, such as documents, tables, analytical results, or experimental datasets. Excellent communication and collaboration skills comfortable working alongside scientists, AI researchers, and product teams. Exposure to NLP, LLMs, embedding generation, or retrieval-augmented workflows. Experience with vector databases / embeddings stores (e.g., OpenSearch) to support semantic search and RAG. Strong problem solving skills, while being Comfortable navigating ambiguity translating loosely defined scientific workflows and user needs into well-engineered search systems. Valued Experience Contributions to open-source search projects (Apache Lucene, Solr, OpenSearch, or similar) or active involvement in the search engineering community. Experience with cheminformatics tools and libraries (e.g., RDKit), including molecular fingerprints, similarity metrics, or substructure search. Prior experience implementing chemical search systems, such as SMILES parsing, normalization, or chemical indexing. Experience with entity resolution, knowledge graphs, or NLP pipelines that enrich search corpora. Experience with large-scale data platforms such as Databricks, Lakehouse architectures, or distributed indexing systems. 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 We are not currently providing visa sponsorship for this position.

Own and maintain documentation pipelines, CI/CD workflows, and infrastructure enabling AI-native content consumption while leading transition to AI-agent based docs and managing editorial quality. | 5+ years in documentation tooling or content engineering with scripting proficiency, experience building LLM-backed workflows, and ability to understand complex codebases. | About TetraScience TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft. In connection with your candidacy, you will be asked to carefully review “The Tetra Way,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you. The Role 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: 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 that makes it 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. You will lead, not just maintain. You will take our existing docs-as-code foundation and AI-assisted documentation workflows and grow them into a docs-as-AI-agents capability that is differentiated for a life-sciences AI platform. You will still own editorial quality and the release-notes cadence, but you will spend most of your time building leverage rather than absorbing work. Own the documentation site and its publishing as software: the docs-as-code repo, the CI/CD publishing pipelines, build performance, and automated link, structure, and quality checks. Build and grow AI-augmented documentation workflows: AI-assisted drafting, summarization, classification, consistency and staleness checks, and a feedback loop that improves generation quality over time, all with human oversight. Build our docs-as-AI-agents position: structure and transform content so AI systems can reliably chunk, index, and reason over it, and stand up and maintain MCP-style interfaces so agents and assistants consume our docs accurately. Generate reference documentation from source (OpenAPI and related specs) and keep docs in lockstep with the platform as code changes. Lower the barrier for internal contributors (PMs, squad leads, engineers) 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 that goes out with every platform release, and run the SME review that keeps it accurate and on time. Own the documentation style guide, hold the review-and-publish gate, and keep the team runbook current so the function is not dependent on any one person. Basics Requirements 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 (for example Python, TypeScript, or JavaScript) and real 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 to build tooling against it. Strong editorial judgment: you can take a dense engineering change and make it clear, correct, and customer-safe. Bachelors or Masters degree in a technical field, or equivalent practical experience. Preferred 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. US 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 We are not currently providing visa sponsorship for this position