Tech Lead – Data Scientist

About the Role

We are looking for a Technical Lead to drive the development of Obsidian's core ontology that powers our groundbreaking unified security config analysis, AI security, and threat detection product.

• Scale this ontology as part of a team of 3-6 software engineers and data scientists to cover hundreds or thousands more enterprise application platforms. Drive automation of repeatable R&D subtasks.
• Become an expert on foundational identity, authentication, authorization, network, and data security concepts. An unhealthy dose of curiosity about the design and administration — technology, people, and process — of complex application platforms such as GitHub, Salesforce, and Workday is a must. You will love exploring rabbit holes into esoteric domain knowledge related to these topics.
• Formulate security problems as data and ML problems, constantly addressing and refining the customer outcome in collaboration with top-flight security teams from Global 1000 companies.

What We’re Looking For

• 6+ years of experience in data science, machine learning, or applied research, preferably with 2+ years in a technical leadership role.
• A track record of shipping production ML or data systems at scale — ideally systems involving ontologies, knowledge graphs, entity resolution, or semantics over heterogeneous data sources.
• Expert-level proficiency in Python and modern ML/data tooling.
• Working knowledge of core security domains, or a strong ability to learn.
• Experience formulating fuzzy business or security problems as concrete ML/data problems:
• able to decompose ambiguous, ambitious problems into well-scoped subproblems and design experiments with statistical rigor.
• comfortable being scrappy and diving deep into vendor documentation, APIs, and audit logs to find the necessary data sources

• Excellent written and verbal communication skills; ability to engage credibly with technical security practitioners at large enterprises.

Staff Site Reliability Engineer

As a Staff SRE at Obsidian, you will define and drive the company-wide reliability vision for a complex, multi-tenant SaaS platform serving enterprise and financial customers. You will operate as a strategic partner to DevOps and Platform Engineering leadership, shaping a unified reliability strategy that scales across the organization.

Your core mandate: ensure Obsidian detects, diagnoses, and communicates system issues before customers are impacted—consistently and predictably.

This is a hands-on technical role that involves architecting and leading the implementation of systems that handle real-world complexity, including upstream SaaS dependencies, sparse and noisy signals, and mission-critical enterprise workloads.

Key Responsibilities

• Reliability Strategy & Architecture - Define and lead long-term reliability strategy across services. Establish end-to-end system visibility frameworks and guide architecture for observability, detection, and resilience.
• Cross-Org Leadership - Partner across teams to embed reliability, standardize SLI/SLOs, and serve as a technical escalation expert.
• Detection & Observability - Build intelligent detection systems (anomaly detection, connector health models) and enable self-service observability.
• Incident Management - Define and evolve a tiered incident communication strategy, improve response practices, and lead postmortems to strengthen reliability and customer trust.
• Execution - Contribute hands-on to system design, monitoring, and debugging across distributed systems and data pipelines.

Required Qualifications

• 5+ years in SRE, Production Engineering, or related roles
• 3+ years operating at a senior or technical leadership level (Staff or equivalent scope)
• Deep expertise in:
• AWS and/or GCP
• Kubernetes and Helm
• Observability stacks (Prometheus, Grafana, or equivalent)
• CI/CD systems (GitLab CI/CD, ArgoCD, etc.)
• Proven experience designing and scaling reliability systems for multi-tenant SaaS platforms
• Strong debugging and systems thinking across distributed microservices and legacy systems
• Demonstrated ability to lead initiatives that improve incident detection, response, and system resilience
• Hands-on engineering approach with a track record of building—not just configuring—reliability systems

Preferred Qualifications

• Experience in B2B SaaS serving enterprise or financial customers
• Familiarity with third-party SaaS connector architectures and ingestion patterns
• Experience building anomaly detection or intelligent alerting systems
• Experience designing customer-facing status pages and incident communication frameworks

Why This Role

• Drive org-wide reliability strategy
• Own and build new detection & observability systems
• Tackle complex distributed systems challenges
• Safeguard critical infrastructure for financial customers

What Success Looks Like

• Issues caught and resolved before customer impact
• Reliability is measurable and continuously improving
• Teams self-serve observability with scalable tools
• Clear, proactive incident communication builds trust
• Reliability becomes a competitive advantage

About the Role

At Obsidian, we relentlessly pursue clarity in a landscape defined by complexity. We’re looking for Security Research Engineers who thrive at the intersection of security research and product engineering. You’ll dig deep into SaaS platforms, craft high-impact product features, and help shape the defensive strategies that protect our customers at scale.

This role is for someone who loves gaining a deep understanding of complex systems, who enjoys thinking like an attacker, and who wants to create category-leading security solutions for Obsidian's customers.

What You’ll Do

• Gain an in-depth understanding of major SaaS or AI platforms to identify critical security insights. 
• Explore and prototype solutions to integrate data across SaaS and AI platforms to identify toxic combinations of risks that can lead to high blast-radius compromises.
• Identify and respond to new attacker techniques against SaaS and AI platforms to build novel approaches to detect or mitigate future attacks.
• Leverage AI to turbo-charge research into SaaS and AI platform security.

What We’re Looking For

Minimum Qualifications

• 5-7 years of experience in the cybersecurity industry with either a research or data focus.
• Experience with data pipelines (dbt, dagster, clickhouse).
• Proficiency in Python/Go and SQL.
• Experience with log processing and anomaly detection.
• Fluency in using AI agents to assist in building prototype solutions.
• Ability to analyze logs and signals from IdPs, cloud, or SaaS apps.

Preferred Qualifications

• Experience with core SaaS platforms such as Google Workspace, Microsoft Office 365, Salesforce, or Workday in a security context.
• Strong understanding of identity systems (Okta, Azure AD/Entra, Google Workspace, etc.) and authentication flows.

Why Join Us

• Protect some of the world's largest organizations 
• Become an expert in SaaS security by learning from the industry’s leader.
• Have a direct impact immediately, and experience Silicon Valley pace from the UK.

About the Role - as a Senior Engineer at Obsidian, you’ll:

• Build or extend data pipelines that power Obsidian’s Agentic AI and supply chain risk products.
• Maintain, improve, and evolve existing systems to ensure performance, resilience, and scalability
• Design and implement APIs and backend services, including multithreaded applications
• Collaborate with product and engineering teams to support key product themes and ensure delivery of high-impact features
• Apply strong software engineering practices to requirements gathering, system design, and code reviews
• Contribute to a fast-moving, collaborative environment where adaptability and teamwork are essential.
• Identify and proliferate best practices in data pipeline design between both the UK and US teams.

What’s in It for You

• You will have direct impact on the core product used by enterprises worldwide
• Work alongside a talented, friendly team in a supportive and collaborative culture
• Grow your skills with opportunities to learn new technologies and engineering practices
• Be part of an innovative, fast-paced environment where your contributions are valued
• Enjoy a hybrid working, with supported remote working and great office spaces in Cheltenham and Manchester

Required Skills & Experience

• 5-7 years of experience in a software engineering role
• Proficiency in one or more modern programming languages such as Python, Go, or SQL
• Experience building backend services, APIs, and multithreaded applications
• Familiarity with containerization and orchestration technologies such as Docker and Kubernetes
• Strong knowledge of relational databases (e.g., Postgres)
• Experience collaborating in team environments and adapting to changing requirements
• Understanding of software design principles and engineering best practices
• Experience with cloud platforms (AWS, GCP), object storage (S3), or event/streaming systems (Kafka, Redis)
• Familiarity with Git for version control and deployment tooling, such as GitLab CI/CD
• Experience in influencing design patterns based on best practices.
• Experience assessing alternative data architecture designs to produce accurate and unbiased recommendations.

Desirable Experience

• Experience with system monitoring and observability tools such as Grafana, Prometheus, or similar platforms
• Understanding of quality engineering (QE) practices across development and testing lifecycles
• Exposure to large-scale distributed systems and performance optimisation
• Experience in forming strong stakeholder relationships to help promote joint working between teams.
• Experience of working alongside both UK and US development teams.

AI Skills & AI-Native Engineering Expectations: As an AI-forward engineering organization, we expect senior engineers to effectively leverage AI tools and understand foundational AI concepts to enhance development efficiency and build AI-ready systems.

AI Engineering Capabilities:

• Leverage AI tools effectively to improve development efficiency and build AI-ready systems.
• Proficient with AI-powered developer tools; able to critically evaluate and refine AI-generated outputs.
• Strong understanding of core AI/ML concepts (LLMs, embeddings, vector databases, inference, evaluation).
• Experience integrating AI/ML APIs and building AI-ready data infrastructure (e.g., for RAG).
• Ensure data quality, governance, observability, reliability, security, and performance in AI-driven systems.

Sr. Staff Site Reliability Engineer

As a Sr. Staff SRE at Obsidian, you will define and drive the company-wide reliability vision for a complex, multi-tenant SaaS platform serving enterprise and financial customers. You will operate as a strategic partner to DevOps and Platform Engineering leadership, shaping a unified reliability strategy that scales across the organization.

Your core mandate: ensure Obsidian detects, diagnoses, and communicates system issues before customers are impacted—consistently and predictably.

This is a hands-on technical role that involves architecting and leading the implementation of systems that handle real-world complexity, including upstream SaaS dependencies, sparse and noisy signals, and mission-critical enterprise workloads.

Key Responsibilities

• Reliability Strategy & Architecture - Define and lead long-term reliability strategy across services. Establish end-to-end system visibility frameworks and guide architecture for observability, detection, and resilience.
• Cross-Org Leadership - Partner across teams to embed reliability, standardize SLI/SLOs, and serve as a technical escalation expert.
• Detection & Observability - Build intelligent detection systems (anomaly detection, connector health models) and enable self-service observability.
• Incident Management - Define and evolve a tiered incident communication strategy, improve response practices, and lead postmortems to strengthen reliability and customer trust.
• Execution - Contribute hands-on to system design, monitoring, and debugging across distributed systems and data pipelines.

Required Qualifications

• 5+ years in SRE, Production Engineering, or related roles
• 3+ years operating at a senior or technical leadership level (Staff or equivalent scope)
• Deep expertise in:
• AWS and/or GCP
• Kubernetes and Helm
• Observability stacks (Prometheus, Grafana, or equivalent)
• CI/CD systems (GitLab CI/CD, ArgoCD, etc.)
• Proven experience designing and scaling reliability systems for multi-tenant SaaS platforms
• Strong debugging and systems thinking across distributed microservices and legacy systems
• Demonstrated ability to lead initiatives that improve incident detection, response, and system resilience
• Hands-on engineering approach with a track record of building—not just configuring—reliability systems

Preferred Qualifications

• Experience in B2B SaaS serving enterprise or financial customers
• Familiarity with third-party SaaS connector architectures and ingestion patterns
• Experience building anomaly detection or intelligent alerting systems
• Experience designing customer-facing status pages and incident communication frameworks

Why This Role

• Drive org-wide reliability strategy
• Own and build new detection & observability systems
• Tackle complex distributed systems challenges
• Safeguard critical infrastructure for financial customers

What Success Looks Like

• Issues caught and resolved before customer impact
• Reliability is measurable and continuously improving
• Teams self-serve observability with scalable tools
• Clear, proactive incident communication builds trust
• Reliability becomes a competitive advantage

About Obsidian Security

Obsidian helps companies figure out what’s happening in their SaaS applications - who’s accessing what, where data is going, and what looks suspicious.

Role Description

You’ll work across the full stack on the Threat product team: browser extension code that hooks into web applications, backend services processing millions of events, and data pipelines feeding our detection engine. One day you’re in TypeScript debugging why a content script isn’t capturing form submissions on some vendor’s weird SPA. The next you’re in Python fixing a Kafka consumer that’s falling behind. Sometimes you’re in Rust optimizing a hot path in the telemetry collector.

Right now, a big focus is shadow AI - enterprises want to know when employees are pasting sensitive data into ChatGPT, Claude, or whatever new LLM chatbot showed up this week. You’ll build the systems that catch this.

What you’ll do

• Own features from “we need to detect X” through production, across extension, backend, and pipeline code
• Write content scripts that interact with web pages and background scripts that coordinate everything
• Build backend services: event ingestion, enrichment, alerting
• Work with security researchers to turn threat intel into working detections
• Help the team get better through code review and design discussions

What we’re looking for

• 8+ years building software, ideally touching a few different areas (not just one stack forever)
• You actually understand how browsers work. DOM APIs, the event loop, how SPAs route, why CORS exists. Not just “I used React.”
• You’ve built browser extensions before. You know the content script/background script split, message passing, manifest v3 limitations.
• Strong TypeScript. Comfortable in Python. Willing to write Rust (or already do).
• You’ve dealt with data at scale: event streaming, pipelines, high-throughput ingestion.
• Backend basics: APIs, Postgres, Elasticsearch, Kafka or similar.
• Can work without someone telling you what to do next.

Bonus points

• You’ve thought about AI security - prompt injection, data exfiltration, that kind of thing
• Background in detection engineering, SIEM, or security ops
• You’ve built or contributed to security tools

Backend Engineer

About the Role - as a Backend Engineer at Obsidian, you’ll:

• Contribute to the development of backend systems that power Obsidian’s core product
• Implement features and services that are scalable, reliable, and performant
• Build and maintain APIs and backend services under the guidance of senior engineers
• Support improvements to existing systems, helping to enhance resilience and maintainability
• Collaborate closely with product managers, designers, and engineers to deliver high-quality features
• Participate in code reviews and technical discussions to continuously improve engineering standards
• Thrive in a fast-paced, collaborative environment where learning and adaptability are encouraged

What’s in It for You

• Contribute to a core product used by enterprises worldwide
• Work alongside a talented, supportive team in a collaborative culture
• Develop your technical skills with mentorship from experienced engineers
• Gain exposure to modern technologies and engineering best practices
• Be part of an innovative, growing company where your work makes a real impact
• Enjoy hybrid working, with supported remote working and great office spaces in Cheltenham and Manchester

Required Skills & Experience

• 2–4 years of experience in a software engineering role
• Proficiency in at least one modern programming language such as Python, Go, or SQL
• Experience building backend services and APIs
• Familiarity with relational databases (e.g., Postgres)
• Understanding of core software engineering principles and clean code practices
• Experience working in a collaborative team environment
• Eagerness to learn, take feedback, and grow technical expertise

Desirable Experience

• Exposure to containerization technologies such as Docker
• Familiarity with cloud platforms (AWS or GCP)
• Experience using Git for version control
• Understanding of distributed systems concepts
• Exposure to CI/CD pipelines

AI Skills & AI-Native Engineering Expectations: As an AI-forward engineering organization, we expect senior engineers to effectively leverage AI tools and understand foundational AI concepts to enhance development efficiency and build AI-ready systems.

AI Engineering Capabilities:

• Leverage AI tools effectively to improve development efficiency and build AI-ready systems.
• Strong understanding of core AI/ML concepts (LLMs, embeddings, vector databases, inference, evaluation).