AppOmni prevents SaaS data breaches by delivering end-to-end SaaS security. Our platform gives security teams clear visibility into posture, access, third-party connections, AI-related activity, and with built-in discovery to identify unsanctioned SaaS and Shadow AI tools. Backed by continuous monitoring and real-time threat detection, AppOmni helps enterprises identify and resolve risks early, keeping their SaaS applications secure. Recognized as a Frost Radar™ 2025 Leader and Great Place To Work®, AppOmni continues to set the standard for innovation and customer value in SaaS security. The largest and fastest-growing global enterprises across industries trust AppOmni to secure their SaaS applications.
Lead Software Engineer
Location
United States
Posted
51 days ago
Salary
$200K - $225K / year
Seniority
Senior
Job Description
Lead Software Engineer
AppOmni
• Design, build, and maintain backend services and APIs to support our GenAI product using Python and FastAPI, ensuring they are scalable, reliable, and secure. • Develop and operate LLM-powered applications and agentic workflows using LangChain, LangGraph, and LangSmith, including tracing, evaluation, and observability. • Develop and manage infrastructure using Terraform, applying infrastructure-as-code (IaC) practices across backend and ML resources. • Build and maintain monitoring and alerting systems to surface service and API health issues early, ensuring reliability and performance. • Handle large datasets to ensure data is processed, ready for model context, and collaborate in the platform data pipeline. • Evaluate and select appropriate tools and technologies and define the overall technical strategy. • Assess and interpret data to gain insights, especially for testing and monitoring purposes. • Build and maintain CI/CD pipelines, including infrastructure-as-code (IaC), and automate deployment and monitoring across backend services and ML workflows. • Continuously improve and automate monitoring and alerts processes. • Optimize infrastructure and services for performance, scalability, reliability, and cost efficiency, and troubleshoot issues across deployment and runtime. • Troubleshoot and resolve issues related to pipeline deployment and performance. • Contribute to the development of internal engineering standards and documentation. • Advocate for engineering best practices and promote a culture of continuous improvement also mentoring and guiding others in the company in this topic. • Understand the requirements of stakeholders and translate them into technical solutions. • Develop robust model monitoring and alerting systems to ensure model performance and identify issues. • Support our mission and vision and embody and demonstrate AppOmni core values of Trust, Transparency, Quality, Customer Focus, and Delivery. Comply with all company policies and governing laws and regulations.
Job Requirements
- At least 8 years of experience in backend centric software development.
- Degree in a relevant field such as Engineering, Computer Science, Data Science, Machine Learning, or a related quantitative discipline.
- Strong programming skills: Proficiency in coding Python for production implementation, including coding best practices, testing, performance considerations, with a good understanding of libraries like Pandas, Polars, Langchain, Langsmith.
- Experience implementing infrastructure for Machine Learning and Generative AI applications.
- Experience in security engineering or another complex domain.
- Excellent communication and collaboration skills to work effectively with Product, Engineering, Field, and other cross-functional teams.
- Experience in Cloud computing: Experience with cloud platforms like AWS, Azure, or GCP for model training and deployment.
- Experience with ML services in Cloud Platforms like VertexAI in GCP.
- Proficient in containerization technologies (Docker, Kubernetes)
- Experience with model monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack).
- Usage of Software engineering practices: Version control, code review, and software design principles.
- Expertise in CI/CD tools (Github, Jenkins, GitLab CI, CircleCI).
- Experience with infrastructure-as-code tools (Terraform, CloudFormation).
- Problem-solving and critical thinking with the ability to analyze complex problems, identify potential issues, and develop innovative solutions.
- Strong self-management skills and able to prioritize tasks and manage time effectively.
- Proactive approach to work and ability to take initiative.
- Nice-to-have: Experience with Databricks.
Benefits
- Generous paid time off
- Paid company holidays
- Paid floating holidays
- Paid parental leave
- Paid sick time
- Paid family leave for applicable states
- Health insurance - medical, dental, and vision with HSA option
- LifeWorks Employee Assistance Program
- Company-provided life insurance
- AD&D, STD/LTD and additional supplemental life insurance options
- 401(k) and Roth retirement saving accounts
- Monthly wellness benefit reimbursement
Related Guides
Related Job Pages
More Full-stack Engineer Jobs
• Drive the technical vision and architecture for Aerial Capture, driving clean code standards, setting technical direction, and making key architectural decisions. • Serve as a primary code contributor, lead projects end-to-end, and proactively coordinate work to ensure predictable delivery, technical quality, and the quick unblocking of teammates. • Raise the technical bar across the team by providing hands-on mentorship, pairing, and timely, direct technical feedback to foster engineer growth. • Take ownership of system health, including reliability and maintainability. Champion the reduction of technical debt and measure outcomes to drive value throughput. • Act as the technical voice for the team in cross-functional forums, communicating decisions, trade-offs, and project status clearly to Engineering Managers and stakeholders.
Senior Software Architect, GPU Networking Research
NVIDIABased in Santa Clara, California, with additional offices throughout the U.S., South America, and Canada, NVIDIA is committed to fostering a work environment wh
• Enhance NVIDIA's future GPU Networking offerings for accelerating AI workloads. • Lead vision, architecture and design of such technologies. • Lead proof-of-concept development to evaluate and drive such technologies. • Identify and evaluate new technologies, innovations and partner relationships for alignment with our technology roadmap and business value. • Work with the community and maintainers to drive strategic technologies.
• Primarily responsible for analyzing data integrity challenges including investigating, correcting, and monitoring data to help identify and address key data issues. • Facilitate effective communication with client project stakeholders regarding project status and recommendations. • Craft client code that is not just efficient, but also performant, testable, scalable, secure, and of the highest quality. • Actively participate in accurate planning and estimation efforts, utilizing project methods and tools. • Proficiently gather requirements and organize/present developed features for clients. • Execute complex activities within the current methodology and quality standards, showcasing success across diverse engagements. • Promote client success across the team by collaborating with engineers, designers, and managers to understand user pain points, anticipate potential problems, and iterate on solutions that drive client success. • Engage in agile software development, including daily stand-ups, sprint planning, team retrospectives, and other governance activities. • Actively participate in the Engineering Practice community, mentoring others through Communities of Practice (CoPs) or on project teams, and supporting the growth of technical capabilities. • Independently drive project delivery within defined architecture, demonstrating autonomy and accountability in all stages from conceptualization to deployment.
• Design, build, and ship high-quality features across the stack, with a focus on creating reusable, maintainable UI components and polished frontends that scale with the platform • Contribute to backend systems to deliver cohesive, end-to-end product experiences • Define and enforce clean API boundaries between frontend and backend systems • Collaborate with teammates to build a platform that supports: • Orchestrating complex deployment workflows • Progressive rollouts across clusters and regions • Automated rollback of failed deployments • Observability into deployment health and performance • Translate complex infrastructure technologies and concepts (e.g., Kubernetes, Argo Rollouts, deployment policies) into intuitive, user-friendly interfaces • Engage directly with engineers across Reddit—conducting user interviews, gathering feedback, and deeply understanding developer workflows—to shape an opinionated “paved path” for releases • Raise the bar for full-stack engineering across the team through code reviews, mentorship, and knowledge sharing • Participate in the team’s on-call rotation and contribute to the reliability of our platform • Continuously grow your technical and non-technical skills




