As a Staff Backend Engineer at Snorkel, you will set the long-term technical direction and strategy for our Expert Contributor (EC) Platform. You will be responsible for defining and driving complex, multi-quarter architectural initiatives that ensure our services are innovative, scalable, and resilient. Your work will bridge the gap between human expertise and machine learning by enabling domain experts to provide high-signal data for training and refining state-of-the-art models.

Main Responsibilities

• Design and develop mission-critical systems for the end-to-end Expert Contributor (EC) lifecycle, focusing on automated onboarding workflows, performance management, and contributor retention.
• Build robust features and integrations with key third-party services, including platforms for assessments and Employer of Record systems.
• Automate supply and allocation logic to efficiently manage and deploy a high volume of ECs to various data collection projects, ensuring optimal coverage and quality.
• Prototype, optimize, and maintain scalable services to power complex data user management pipelines.
• Set the strategy and architecture for build systems, testing frameworks, and CI/CD pipelines.
• Lead the transition from scheduled releases to a robust, automated continuous deployment framework, taking end-to-end ownership of the release pipeline.
• Build proactively with empathy for both customers and subject matter experts using our tools.
• Mentor and guide Senior and Mid-level engineers on technical design, best practices, and project execution across multiple teams.
• Partner with cross-functional teams to design and deliver improvements to dev-infra, release processes, and internal tooling.
• Engage with product managers, designers, and ML experts to create a phenomenal user experience for data acquisition and refinement.

Qualifications

• 8+ years of software engineering experience developing performant, intuitive, and scalable web application architectures and 2+ years working at a Staff level or equivalent
• Strong background in developer productivity, distributed systems, and cloud platforms (AWS preferred).
• Expertise designing REST for internal services and developers.
• Experience developing and shipping enterprise software products, specifically those focused on data collection, or machine learning applications.
• Track record of leading complex engineering initiatives, influencing stakeholders, and delivering measurable impact.
• Ability to work in a fast-paced environment with strong technical communication skills.

Nice to Have

• Experience in hyper-growth startup environments or scaling engineering orgs.
• Experience with AI development workflows, AI-assisted code generation, or SRE automation or strong excitement to learn.
• Prior experience as a Tech Lead Manager (TLM) or equivalent role with a focus on cross-functional technical leadership and mentorship.

Work Schedule

• Work a hybrid schedule with three days per week in our Redwood City HQ or the SF office.

• Design and develop key interfaces for our expert data collection workflows, focusing on high-efficiency labeling, data analysis, and sophisticated visualization tools.
• Prototype, optimize, and maintain scalable services to power complex data collection pipelines and expert-in-the-loop workflows.
• Build proactively with empathy for both our customers and the subject matter experts using our tools, constantly iterating to balance innovative research with practical solutions.
• Engage with product managers, designers, and ML experts to create a phenomenal user experience for data acquisition and refinement.
• Collaborate with engineers to bring consistency and high standards to codebases, infrastructure, and processes.
• Work a hybrid schedule with three days per week in our Redwood City HQ or the SF office.

• 6+ years of professional full-stack experience developing performant, intuitive, and scalable web application architectures.
• Experience developing and shipping enterprise software products, specifically those focused on data collection, annotation, or machine learning applications.
• Experience prototyping and iterating on user interfaces with modern React (ES7+, React hooks, TypeScript).
• Expertise designing REST APIs for internal services and developers.
• Ability to work in a fast-paced environment with strong technical communication skills.
• Self-motivation, a positive mental attitude, and an eagerness to learn in the rapidly evolving AI landscape.

We’re looking for a Software Engineer in Test who thrives in fast-moving, high-intensity environments and enjoys turning ambiguous problems into reliable, scalable systems. In this role, you’ll go beyond traditional QA—fine tuning test infrastructure, tooling, and processes that directly accelerate engineering velocity and product quality.

What You’ll Do

• Refine and evolve testing infrastructure and tooling that enables engineers to ship high-quality features at scale
• Design, implement, and maintain automated testing systems 
• Create internal tools that improve developer productivity and shorten iteration cycles
• Partner closely with DevOps to optimize test execution and reliability within CI/CD pipelines
• Drive best practices in testing, observability, and release confidence across the engineering org

What We’re Looking For

• • 3-5 years experience scaling test frameworks, infrastructure, or developer tooling
  • Proficiency in TypeScript and/or Python
  • Experience with CI/CD systems such as CircleCI, Buildkite, or similar tools
  • Ability to operate in ambiguous environments and bring structure to complex problems
  • A systems mindset—you think in terms of reliability, scalability, and long-term maintainability

Why Snorkel AI

• Work at the forefront of AI development and evaluation
• Collaborate with top AI labs and innovative enterprise teams
• Build systems that directly impact how cutting-edge AI is developed and deployed

The Core Services team within Snorkel AI's Infrastructure organization will own the data platform that powers everything at Snorkel — the pipelines, access layers, event systems, governance, and compute infrastructure that every product team and customer deployment depends on. We are a small team with a large surface area, and we are in the middle of a foundational architecture shift: moving from a single-database data path to a multi-source, event-driven platform with dedicated stores for different workloads (transactional data in Postgres/RDS, analytical data in Snowflake, bulk storage in S3, metrics platform). The decisions being made now will define how data flows at Snorkel for years. You will be making them.

You’ll also shape our AI-native development workflow, contribute in modernizing CI/CD workflow (Buildkite, GitHub Actions), and integrate AI SRE tooling. Your work will directly accelerate developer velocity, reliability, and product quality across the company

What You'll Do

• Build and maintain the shared data access library and SDKs that Platform, Packaging, and Dataset API teams use to read from and write to multiple data sources (Snowflake, S3, RDS). Design interfaces that abstract source-level complexity while providing built-in auth, RBAC enforcement, pagination, and query governance.
• Design and implement event-driven data flows using event brokers,  CDC connectors, schema registry, event routing, dead letter queues. Make sure events flow reliably and failures are visible and recoverable.
• Build the systems that track how data moves through the platform (lineage), enforce who can access what (governance and RBAC), and log what happened (auditing). This includes PII handling, retention policy enforcement, and audit infrastructure for enterprise and federal compliance.
• Instrument the data platform with OpenTelemetry, define and monitor SLOs for query latency and pipeline success rates, and build alerting that catches issues before they become incidents. You will be on-call for the systems you build.
• Contribute to infrastructure cost visibility and optimization -  query cost estimation, workload right-sizing, and routing data to the most cost-effective storage tier for its access pattern.

What You'll Bring

• 8+ years building platform infrastructure, data infrastructure, data platforms, or backend systems with significant data components. You have built and operated pipelines, data access layers, or ETL/ELT systems in production.
• Strong proficiency in Python. Our stack is Python-heavy across Prefect, FastAPI, dbt, and the SDK layer.
• Hands-on experience with SQL and at least two of: Snowflake, Redshift, Postgres. You understand the performance characteristics of each and can write queries that don't bring down production.
• Experience with AWS — S3, RDS, EKS, EventBridge, IAM. Comfortable working in a Terraform-managed environment
• Experience with Kubernetes. Our workloads run on EKS and you will deploy, debug, and scale services on K8s.
• Familiarity with data orchestration tools (Prefect, Airflow, or Dagster) and transformation frameworks (dbt).
• Understanding of data governance concepts — RBAC, PII handling, audit logging, data lineage.
• Fluency with AI-assisted development tools (Claude Code, Cursor, or similar). This is a hard requirement — the team uses these tools daily and we expect engineers to leverage them for code generation, debugging, and investigation.

Nice to Have

• Experience building shared libraries or SDKs consumed by multiple teams — versioning, backwards compatibility, migration support.
• Experience with event-driven architectures — CDC, event buses, schema registries, at-least-once delivery semantics.
• Experience with OpenTelemetry, ClickHouse, or similar observability infrastructure.
• Prior work in regulated environments (SOC 2, FedRAMP, HIPAA) where compliance requirements shaped system design.
• Experience with Ray for distributed compute workloads.

About the Team 

We are looking for a Senior AI/ML Engineer to add to our AI Platform team. This is a role for someone who wants to operate at the nexus of distributed systems, LLM infrastructure, synthetic data, and agentic orchestration. Our platform enables an ecosystem of expert contributors to create the datasets and evaluation environments that frontier models rely on to improve. We combine a decade of academic research with production-grade engineering to help customers build differentiated, high-performance AI systems faster than ever before.

About the Role

• Architect the core platform that powers synthetic data generation, agentic workflows, RL environments, and scalable LLM operations
• Design and evolve the APIs, compute services, and orchestration layers that empower internal and customer-facing applications
• Generate and refine synthetic data at massive scale
• Create and evaluate agentic systems that reason, act, and improve over time
• Provision RL training environments and simulation frameworks for next-generation AI agents
• Deploy robust benchmarks, datasets, and automated labeling pipelines to accelerate model development
• Run LLMs and multi-agent systems efficiently, reliably, and cost-effectively across cloud and hybrid environments
• Work a hybrid schedule with three days per week in our Redwood City HQ or the SF office.

About You

• 5 years of experience building customer-facing, cloud-native software systems
• Deep experience with AI/ML pipelines, LLM-based systems, or agentic workflows
• Experience with distributed computing, large-scale data systems, or orchestration frameworks
• Experience at high-growth technology startups
• Experience building software products for large enterprise customers
• Expertise in Python and cloud platforms (AWS, GCP, or Azure)
• Strong understanding of production web-scale systems: monitoring, telemetry, reliability, performance, debugging, and triage

As a Senior Backend Engineer at Snorkel, you will deliver robust features that power our Expert Contributor (EC) Platform. You will have full ownership and responsibility for building, shipping, and maintaining innovative, scalable services and complex features as well as building and maintaining integrations with various vendors. Your work will bridge the gap between human expertise and machine learning by enabling domain experts to provide high-signal data for training and refining state-of-the-art models.

Main Responsibilities

• Design and develop mission-critical systems for the end-to-end Expert Contributor (EC) lifecycle, focusing on automated onboarding workflows, performance management, and contributor retention.
• Build robust features and integrations with key third-party services, including platforms for assessments and Employer of Record systems.
• Automate supply and allocation logic to efficiently manage and deploy a high volume of ECs to various data collection projects, ensuring optimal coverage and quality.
• Prototype, optimize, and maintain scalable services to power complex data user management pipelines.
• Set the strategy and architecture for build systems, testing frameworks, and CI/CD pipelines.
• Lead the transition from scheduled releases to a robust, automated continuous deployment framework, taking end-to-end ownership of the release pipeline.
• Build proactively with empathy for both customers and subject matter experts using our tools.
• Collaborate with engineers to bring consistency and high standards to codebases, infrastructure, and processes.
• Engage with product managers, designers, and ML experts to create a phenomenal user experience for data acquisition and refinement.

Qualifications

• 8+ years of software engineering experience
• 6+ years of professional experience developing performant, intuitive, and scalable web application architectures.
• Strong background in developer productivity, distributed systems, and cloud platforms (AWS preferred).
• Expertise designing REST for internal services and developers.
• Experience developing and shipping enterprise software products, specifically those focused on data collection, annotation, or machine learning applications.
• Track record of leading complex engineering initiatives, influencing stakeholders, and delivering measurable impact.
• Comfortable working with:
• Infra & deployment technologies: Terraform, Docker, Kubernetes.
• CI/CD systems: CircleCI, Buildkite, GitHub Actions, Helm.
• Ability to work in a fast-paced environment with strong technical communication skills.
• Self-motivation, a positive mental attitude, and an eagerness to learn in the rapidly evolving AI landscape.

Nice to Have

• Experience in hyper-growth startup environments or scaling engineering orgs.
• Experience with AI development workflows, AI-assisted code generation, or SRE automation or strong excitement to learn.
• Prior experience as a Tech Lead, Team Lead, or Hands on Engineering Manager.

Work Schedule

• Work a hybrid schedule with three days per week in our Redwood City HQ or the SF office.

The Core Services team within Snorkel AI's Infrastructure organization will own the data platform that powers everything at Snorkel — the pipelines, access layers, event systems, governance, and compute infrastructure that every product team and customer deployment depends on. We are a small team with a large surface area, and we are in the middle of a foundational architecture shift: moving from a single-database data path to a multi-source, event-driven platform with dedicated stores for different workloads (transactional data in Postgres/RDS, analytical data in Snowflake, bulk storage in S3, metrics platform). The decisions being made now will define how data flows at Snorkel for years. You will be making them.

You’ll also shape our AI-native development workflow, contribute in modernizing CI/CD workflow (Buildkite, GitHub Actions), and integrate AI SRE tooling. Your work will directly accelerate developer velocity, reliability, and product quality across the company

What You'll Do

• Build and maintain the shared data access library and SDKs that Platform, Packaging, and Dataset API teams use to read from and write to multiple data sources (Snowflake, S3, RDS). Design interfaces that abstract source-level complexity while providing built-in auth, RBAC enforcement, pagination, and query governance.
• Design and implement event-driven data flows using event brokers,  CDC connectors, schema registry, event routing, dead letter queues. Make sure events flow reliably and failures are visible and recoverable.
• Build the systems that track how data moves through the platform (lineage), enforce who can access what (governance and RBAC), and log what happened (auditing). This includes PII handling, retention policy enforcement, and audit infrastructure for enterprise and federal compliance.
• Instrument the data platform with OpenTelemetry, define and monitor SLOs for query latency and pipeline success rates, and build alerting that catches issues before they become incidents. You will be on-call for the systems you build.
• Contribute to infrastructure cost visibility and optimization -  query cost estimation, workload right-sizing, and routing data to the most cost-effective storage tier for its access pattern.

What You'll Bring

• 4+ years building platform infrastructure, data infrastructure, data platforms, or backend systems with significant data components. You have built and operated pipelines, data access layers, or ETL/ELT systems in production.
• Strong proficiency in Python. Our stack is Python-heavy across Prefect, FastAPI, dbt, and the SDK layer.
• Hands-on experience with SQL and at least two of: Snowflake, Redshift, Postgres. You understand the performance characteristics of each and can write queries that don't bring down production.
• Experience with AWS — S3, RDS, EKS, EventBridge, IAM. Comfortable working in a Terraform-managed environment
• Experience with Kubernetes. Our workloads run on EKS and you will deploy, debug, and scale services on K8s.
• Familiarity with data orchestration tools (Prefect, Airflow, or Dagster) and transformation frameworks (dbt).
• Understanding of data governance concepts — RBAC, PII handling, audit logging, data lineage.
• Fluency with AI-assisted development tools (Claude Code, Cursor, or similar). This is a hard requirement — the team uses these tools daily and we expect engineers to leverage them for code generation, debugging, and investigation.

Nice to Have

• Experience building shared libraries or SDKs consumed by multiple teams — versioning, backwards compatibility, migration support.
• Experience with event-driven architectures — CDC, event buses, schema registries, at-least-once delivery semantics.
• Experience with OpenTelemetry, ClickHouse, or similar observability infrastructure.
• Prior work in regulated environments (SOC 2, FedRAMP, HIPAA) where compliance requirements shaped system design.
• Experience with Ray for distributed compute workloads.

About the Role

We are seeking a Security Engineer to evolve Snorkel's security posture across our cloud infrastructure, developer platform, and product ecosystem. You will partner with the security lead to secure cloud environments, build security automation, guide cross-functional initiatives, and embed security into our engineering workflows.

You will work across infrastructure, platform, product, and application teams to ensure our systems scale securely and meet the bar required for modern, cloud-native, compliance-focused environments. This is a high-impact role where your ability to work effectively with others matters as much as your technical depth.

You do not need to meet every requirement listed below to apply. If you bring solid fundamentals in cloud security and are motivated to grow into the gaps, we encourage you to apply.

Key Responsibilities

• Build and scale Infrastructure as Code (IaC) governance strategies that embed security while enabling developer velocity
• Operate and tune Cloud Security Posture Management (CSPM) tooling and coordinate remediation through engineering teams
• Investigate security events, triage incidents, identify root causes, and own remediation through resolution
• Architect secure AWS cloud account structures — landing zones, multi-account patterns, network segmentation, and cross-account role strategies
• Design and implement network security architectures using security groups, Network Access Control Lists (NACLs), subnetting, routing layers, and egress controls
• Establish secure-by-default design patterns across Kubernetes and containerized workloads
• Design, maintain, and govern Identity and Access Management (IAM) role & policy architectures for both human and machine identities
• Implement encryption everywhere — data-at-rest, data-in-transit, and key rotation using AWS Key Management Service (KMS) and related services
• Conduct threat modeling, architecture reviews, and secure design assessments for new and existing systems
• Assess and secure AI/ML product architectures, including trust boundaries, API boundaries, and data flow through training and inference pipelines
• Build secure automation through Python, AWS-native services, and policy-as-code frameworks
• Own complex security projects end-to-end — from discovery and design docs to implementation, rollout, and long-term ownership
• Align cloud security strategy with relevant frameworks (NIST CSF, ISO 27001, SOC 2, CIS benchmarks)

Professional Skills

Security at a growing startup is not a solo effort. This role succeeds by making the entire organization more secure through the people and teams around you. These skills are not secondary to technical ability — they shape whether security work actually lands and delivers lasting impact.

Communication & Influence

• Communicates security risks, trade-offs, and recommendations clearly to both technical and non-technical audiences
• Writes concise, structured technical documentation — design docs, runbooks, postmortems, and policy proposals that others can act on without follow-up clarification
• Builds alignment on security priorities across teams without relying on positional authority — a small security team cannot mandate adoption; it must earn buy-in

Cross-Functional Partnership

• Builds trust with engineering, product, and infrastructure teams by proposing solutions that balance security posture with developer velocity — security controls that teams resist or work around deliver zero impact
• Defaults to collaboration over enforcement — works with teams to find the right path forward rather than handing down requirements
• Seeks to understand the workflows, constraints, and incentives of partner teams before proposing changes — the best security solution is one the team will actually implement and maintain

Ownership & Judgment

• Comfortable with broad ownership, context-switching, and exercising judgment without a large support structure — this role requires self-direction, not delegation
• Exercises sound judgment on when to push hard on a security requirement versus when to accept managed risk with compensating controls
• Balances thoroughness with pragmatism — delivers iterative security improvements that compound over time rather than waiting for perfect solutions that never ship
• Manages multiple concurrent initiatives with clear ownership, status communication, and escalation when blocked

Teaching & Growth

• Multiplies impact by making others better — equips engineers across the organization to build securely by default through training, code review feedback, and accessible documentation
• Frames security guidance as enablement rather than enforcement — helps teams understand the why behind requirements so they can make sound security choices on their own
• Consistently seeks feedback, stays current on evolving threats and technologies, and treats gaps in knowledge as opportunities — a coachable mindset and commitment to continuous learning are essential in a domain that changes constantly

Technical Skills & Experience

The skills below are grouped into what we consider foundational for this role and additional areas where you will contribute and grow. Depth across every area is not expected — we value solid fundamentals and the ability to learn.

Foundational

• Programming skills in Python, Go, or similar languages, with the ability to build security tooling and automation
• Experience building and operating systems at scale in cloud-native, containerized environments
• Proficiency with Infrastructure as Code (Terraform): writing modules, CI/CD pipelines, deployment governance, and security reviews
• AWS cloud architecture: multi-account strategies, landing zones, environment isolation, and cross-account role design
• Identity and Access Management (IAM): role and policy architectures, least privilege, human and machine identity patterns
• Network security: security groups, Network Access Control Lists (NACLs), Virtual Private Cloud (VPC) design, subnet segmentation, routing layers, and egress controls

Additional Areas You'll Contribute To

• Threat modeling and secure design assessments for new and existing systems
• Encryption and key management: data-at-rest, data-in-transit, key rotation using AWS KMS, Secrets Manager, or HashiCorp Vault
• Container and OS hardening: secure base images, hardened Amazon Machine Images (AMIs), runtime protections
• Cloud Security Posture Management (CSPM) tooling — deployment, tuning, and coordinating remediation workflows through engineering teams
• Security event investigation: triage, root cause assessment, and remediation ownership
• Vulnerability management lifecycle: scanning, prioritization, tracking, and closure
• AI/ML security: awareness of risks specific to AI/ML systems (prompt injection, data poisoning, model extraction, training data protection) and ability to assess trust boundaries in AI product architectures
• Compliance and security frameworks: NIST CSF, ISO 27001, SOC 2, CIS benchmarks
• Designing secure architectures for high-growth SaaS or cloud-native environments

Preferred Experience (Nice-to-Have)

• Secure development lifecycle (SDLC) practices: static analysis (SAST), software composition analysis (SCA), software bill of materials (SBOM) automation, secrets scanning, or bug bounty program management
• Incident response: digital forensics and incident response (DFIR), forensic investigation, or on-call security operations
• Detection engineering: Security Information and Event Management (SIEM) platforms, correlation rules, alert tuning, or Security Orchestration, Automation and Response (SOAR) playbooks
• Offensive security: penetration testing, red team exercises, or adversarial testing of AI systems
• Multi-cloud environments (GCP, Azure) in addition to AWS
• Zero-trust architecture practices and secure workspace design
• Data loss prevention (DLP) strategies for protecting training data and customer data

What You'll Impact

You will embed security from code to cloud — ensuring our systems, data, customer environments, and developer workflows operate securely at scale. This role carries broad influence, high ownership, and the opportunity to shape modern cloud security architecture across the organization.

About the Role

We are hiring a senior engineer to join our Developer Experience (DevEx) team — a small, high-impact group responsible for elevating how engineering builds, tests, ships, and collaborates. This role is ideal for someone who wants to own strategy, influence engineering-wide workflows, and grow into a Tech Lead Manager (TLM)

You’ll shape our AI-native development environment, modernize CI/CD platforms (CircleCI, Buildkite, GitHub Actions), integrate AI SRE tooling, and mentor engineers across levels. Your work will directly accelerate developer velocity, reliability, and product quality across the company.

What You’ll Do

• Set the strategy and architecture for our local development environment, build systems, testing frameworks, CI/CD pipelines, and AI-assisted coding workflows (Claude Code, Claude MD-in-repo workflows)
• Own the CI health and experience, maintain metrics to track CI health, developer productivity, effective usage of AI and build roadmap to constantly improve
• End-to-end ownership of our release pipeline and lead the transition from scheduled releases to a robust, automated continuous deployment framework
• Deep experience and opinion in standardizing for effective usage of AI coding and reviewing agents for faster development, review and incident investigation
  
  
• Ship a clear multi-quarter DevEx roadmap and lead cross-team adoption
• Mentor and technically guide engineers within and outside of the team with best practices to improve quality and velocity; potential to grow into TLM ownership as the team grows
• Partner with cross-functional teams to design and deliver improvements to dev-infra, release processes, and internal tooling.
  
  
• Proactively identify bottlenecks and drive large-scale DX initiatives — e.g., cutting flaky tests, improving PR iteration speed, increasing automated test coverage, and reducing infra cost
  
  
• Present plans, tradeoffs, and progress to engineering leadership; serve as a thought partner for org-wide developer experience strategy.
  
  
• Champion experimentation and roll-out of AI-native development workflows, coding assistants, test-generation tools, and autonomous CI bots.
  
  

What You’ll Bring

• 8+ years of software engineering experience, including deep ownership of build, test, or CI/CD systems
• Proven experience owning and evolving CI/CD systems for large-scale codebases, focusing on reliability, scalability, and developer productivity
  
  
• Demonstrated experience defining and executing roadmaps for developer experience initiatives and internal engineering tooling
  
  
• Deep understanding of how to effectively integrate AI agents into the development workflow to accelerate engineering velocity and improve developer experience.
  
  
• Strong background in developer productivity, distributed systems, and cloud platforms (AWS preferred)
  
  
• Track record of leading complex engineering initiatives, influencing stakeholders, and delivering measurable impact
  
  
• Excellent communication skills; able to translate technical constraints into clear plans for non-technical audiences
  
  
• Comfortable working with:
  
  
• Infra & deployment technologies: Terraform, Docker, Kubernetes
  
  
• CI/CD systems: CircleCI, Buildkite, GitHub Actions, Helm
  
  
• Build systems like Poetry, pip, uv
  
  
• Experience designing and operating large-scale developer workflows and improving engineering best practices.
  
  

Nice to Have

• Experience in hyper-growth startup environments or scaling engineering orgs.
• Experience with AI development workflows, AI-assisted code generation, or SRE automation or strong excitement to learn.
• Prior experience as a Tech Lead, Team Lead, or Hands on Engineering Manager.