Staff Software Engineer

About the Role - as a Staff Software Engineer at Obsidian, you'll:

Own meaningful product and platform work across Obsidian's engineering stack, with scope that extends beyond a single team. This is a generalist role for someone who can move between backend services, data flows, APIs, product features, integrations, and production systems without getting stuck at the boundaries between them, and who can set technical direction that other engineers and teams align to.

You'll work on systems that help customers understand activity, risk, and threats across their SaaS environments. Some problems will be well-defined. Others will start as a customer need, a security signal, or a vague product idea that needs technical shape. You should be comfortable turning that ambiguity into an architecture, a multi-team plan, and working software — and comfortable being the person others look to when the technical path forward is unclear.

What you'll do

• Own features and system architecture from problem definition through production, at a scope spanning multiple teams or the broader platform
• Design and build backend services, APIs, data processing workflows, integrations, and product-facing capabilities
• Set technical direction and architectural standards that other engineers and teams build against
• Work with product managers, designers, security researchers, and engineers to turn customer needs into shipped software
• Improve the performance, reliability, scalability, and observability of existing systems, and identify systemic risks before they become incidents
• Make practical technical decisions with organization-wide impact and explain the tradeoffs clearly to both technical and non-technical stakeholders
• Raise engineering standards through code reviews, design discussions, mentoring senior and mid-level engineers, and documentation
• Debug the hardest production issues and drive teams to durable fixes, not just short-term patches
• Use AI-powered tools effectively while maintaining high standards for correctness, security, and maintainability

What's in It for You

• Direct, high-leverage impact on a core security product used by enterprises worldwide
• Variety across backend engineering, data pipelines, SaaS integrations, detection systems, cloud infrastructure, and customer-facing workflows
• A chance to define the technical approach to current security problems around SaaS, identity, data movement, and AI usage
• Strong peers across product, engineering, security research, and go-to-market teams
• A fast-moving environment where staff/principal engineers are expected to own ambiguous problems, influence direction across teams, and ship

Required Skills & Experience

• 8+ years of experience in a software engineering role, with a track record of increasing technical scope and impact
• Strong proficiency in one or more modern programming languages such as Python, Go, TypeScript, or SQL
• Demonstrated experience designing and building backend services, APIs, distributed systems, data processing workflows, or production product features at scale
• Deep understanding of relational databases such as Postgres, including performance and scaling tradeoffs
• Experience with cloud platforms such as AWS or GCP, including cost, reliability, and architecture tradeoffs
• Familiarity with containerization and orchestration technologies such as Docker and Kubernetes
• Experience with event-driven or streaming systems such as Kafka, Redis, or similar technologies
• Strong ability to reason about system design, performance, reliability, security, and operational tradeoffs across multiple systems and teams
• Experience setting technical direction and leading complex, cross-team technical initiatives without needing formal authority
• Strong communication skills in code reviews, design discussions, and cross-functional planning, including with senior stakeholders

Desirable Experience

• Experience with observability and monitoring tools such as Grafana, Prometheus, or similar platforms
• Experience with CI/CD pipelines and deployment tooling such as GitLab CI/CD
• Deep exposure to large-scale distributed systems, high-throughput ingestion, or data pipeline architecture
• Background or interest in security, SaaS platforms, identity, threat detection, or data protection
• Experience working across multiple engineering teams or across geographically distributed teams
• Experience mentoring engineers, including senior engineers, and helping teams improve technical practices
• Experience evaluating AI-generated code and using AI tools as part of an engineering workflow

AI Skills & AI-Native Engineering Expectations

As an AI-forward engineering organization, we expect staff/principal engineers to effectively leverage AI tools and understand foundational AI concepts to improve development efficiency, build AI-ready systems, and set the standard for how their teams use AI tools responsibly.

AI Engineering Capabilities

• Leverage AI tools effectively to improve development efficiency and build AI-ready systems
• Critically evaluate, test, and refine AI-generated outputs before they reach production
• Understand core AI/ML concepts such as LLMs, embeddings, vector databases, inference, and evaluation
• Experience integrating AI/ML APIs or building systems that support AI-driven product workflows
• Ensure quality, observability, reliability, security, and performance in systems that use or support AI capabilities
• Help establish org-wide norms and best practices for AI-assisted engineering