Software Engineering Technical Lead, Platform - Primitives & Registry

TetraScience is the Scientific Data and AI Cloud company with a mission to radically improve and extend human life. The world's leading pharmaceutical and biotech organizations use the Tetra Data Platform to make scientific data accessible, actionable, AI-ready, and compliant across the full R&D lifecycle.

Scientific data is uniquely complex. It comes from thousands of instruments, applications, assays, file formats, schemas, workflows, and organizations. TetraScience provides the infrastructure to collect, harmonize, govern, analyze, and activate that data so scientists and scientific builders can move faster with greater confidence.

We are building the platform layer for a new generation of scientific software: reusable scientific Functions, governed Data Resources, composable Workflow Manifests, and a Registry that makes scientific logic discoverable, versioned, auditable, and safe to reuse.

We are hiring a Software Engineering Technical Lead to help design and build TetraScience’s next-generation Primitives and Registry platform.

This is a deeply hands-on IC engineering leadership role. You’ll spend much of your time architecting, designing and writing code, designing APIs and data models, reviewing implementations, and operating distributed services. At the same time you’ll serve as technical lead for a small, high leverage platform team, shaping architecture, mentoring engineers, and helping turn ambiguous platform strategy into reliable software.

This role sits at the intersection of developer platforms, data contracts, workflow systems, and product engineering. You will design and build the systems that enable internal and external builders to publish, version, discover, validate, govern, and compose scientific logic across the Tetra OS.

As AI dramatically lowers the cost of software components, AI agents are becoming first-class builders alongside human developers. Today, TetraScience has existing artifact-management systems and package/distribution infrastructure. We are evolving that foundation to support new platform primitives and rapid expansion. You won’t reinvent package management, and you’ll use best in class tools where appropriate. You will build the Tetra-specific contract, governance, lineage, and developer experience layers that make scientific workflows reusable and trustworthy.

- 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.

What You’ll Bring

- Significant experience building production platform, infrastructure, developer-experience, artifact, registry, workflow, or data-platform systems.

- Strong hands-on engineering ability; you are comfortable spending most of your time writing, reviewing, and operating production code.

- Experience owning architecture and implementation for ambiguous, cross-cutting systems used by multiple engineering teams.

- Deep understanding of package, artifact, and registry concepts such as semantic versioning, dependency resolution, immutable versions, artifact promotion, deprecation, and supply-chain integrity.

- Strong product engineering judgment: you can make technically rigorous systems usable for real builders.

- Strong instincts for security, governance, safety, and observability in systems where human developers, automation, and AI agents are all first-class creators of reusable components.

- Excellent technical communication and leadership: you can explain complex architecture clearly, make pragmatic build-versus-buy decisions, mentor engineers, and operate well under ambiguity.

Strong Signals

We would be especially interested if you have deep experience building any of the following:

- Package, artifact, or registry systems such as PyPI, NPM, Maven, JFrog Artifactory, OCI registries, internal package indexes, schema registries, data catalogs, model registries, workflow registries, lineage systems, or metadata platforms.

- Developer-platform tooling such as SDKs, CLIs, CI/CD systems, internal developer portals, or self-service release systems.

- Workflow and orchestration systems such as Argo, Airflow, Dagster, Temporal, Kestra, Prefect, Databricks workflows, or similar.

- Data contract, lineage, governance, provenance, or regulated-workflow concepts, especially in scientific, healthcare, financial, or other high-trust environments.

- Building platforms for internal developers, external developers, field teams, data/ML engineers, technical customer teams, or AI agents.

- Leading migrations from bespoke scripts or manual release processes to governed, reusable, observable platform workflows.

What Success Looks Like

In your first several months, you will:

- Understand the current artifact-management and primitive-platform landscape.

- Define a clear architecture for how existing artifact systems evolve into a unified registry and developer workflow.

- Write and ship meaningful production code for early platform capabilities.

- Baseline and improve the core domain model for components, versions, implementations, dependencies, governance tiers, and compatibility.

- Deliver early technical slices that allow builders to publish and consume new primitive types safely.

- Create alignment across engineering and product teams on what we are building, what we are reusing, and what we are explicitly not building.

- Help the team move from bespoke, tribal workflows toward a self-service, governed, observable platform.

- Improve engineering execution through design clarity, implementation quality, code review, documentation, and operational ownership.

Longer term, your work will help TetraScience make scientific logic reusable across customers, workflows, and AI agents. Builders should be able to publish once, validate once, discover easily, compose safely, and operate with full traceability.

Why This Role Is Different

In an AI-native development environment, trust boundaries become even more important. The platform must treat AI agents as first-class builders while making it easy to generate and reuse components, but hard to accidentally publish unsafe, unobservable, poorly governed, or scientifically misleading logic.veloper-platform roles optimize for software delivery. This role also has to account for scientific meaning, data lineage, regulated workflows, and the trust boundary between exploratory and validated science.

A library in our platform is not just a code package. It may represent a scientific calculation, transformation, model invocation, validation rule, or workflow step. Data is not just a table or file. It may represent a schema contract, a governed scientific data type, or an immutable, lineaged data realization. A workflow is not just an execution graph. It is a scientific process that must be reviewed, reused, governed, and audited.

The right person will be excited by that complexity, disciplined enough to keep the architecture simple where it can be simple, and hands-on enough to build the system rather than only describe it.

• 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.