Senior Software Engineer

Obsidian Security

About The Position

Founded in 2017, Obsidian Security was created to close a critical gap: securing the SaaS applications where modern business happens—platforms like Microsoft 365, Salesforce, and hundreds more. Backed by top investors including Greylock, Norwest Venture Partners, and IVP, we’ve built a complete SaaS security platform to reduce risk, detect and respond to threats, and prevent breaches at the source. Our team includes leaders who helped define the categories of endpoint and identity security at CrowdStrike, Okta, Cylance, and Carbon Black. Now, we’re transforming how SaaS is secured—in the era of agentic AI. Today, Obsidian is trusted by global enterprises like Snowflake, T-Mobile, and Pure Storage. We protect more than 200 organizations across North America, Europe, the Middle East, Southeast Asia, Australia, and New Zealand—including many of the world’s largest Fortune 1000 and Global 2000 companies. With strong global momentum, a growing partner ecosystem including SentinelOne, Databricks, and Google Cloud, and a major fundraise on the horizon, we’re scaling quickly toward long-term growth and IPO readiness. Join us as we define the future of SaaS security! As a Senior Software Engineer at Obsidian, you’ll: Own meaningful product and platform work across Obsidian’s engineering stack. 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. 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 a design, a plan, and working software.

Requirements

5+ years of experience in a software engineering role
Strong proficiency in one or more modern programming languages such as Python, Go, TypeScript, or SQL
Experience designing and building backend services, APIs, distributed systems, data processing workflows, or production product features
Strong understanding of relational databases such as Postgres
Experience with cloud platforms such as AWS or GCP
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
Ability to reason about system design, performance, reliability, security, and operational tradeoffs
Experience leading technical work across a team without needing formal authority
Strong communication skills in code reviews, design discussions, and cross-functional planning
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
Ensure quality, observability, reliability, security, and performance in systems that use or support AI capabilities

Nice To Haves

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
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 and helping teams improve technical practices
Experience evaluating AI-generated code and using AI tools as part of an engineering workflow
Experience integrating AI/ML APIs or building systems that support AI-driven product workflows is a plus

Responsibilities

Own features and system improvements from problem definition through production
Design and build backend services, APIs, data processing workflows, integrations, and product-facing capabilities
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
Make practical technical decisions and explain the tradeoffs clearly
Help raise engineering standards through code reviews, design discussions, mentoring, and documentation
Debug production issues and help teams get to durable fixes, not just short-term patches
Use AI-powered tools effectively while maintaining high standards for correctness, security, and maintainability