Senior Software Engineer, Backend/Distributed Systems - AI Security & Governance

Omnissa•Atlanta, GA

2d•$141,000 - $250,000•Hybrid

About The Position

Omnissa is hiring a Senior Software Engineer for Elara, a new product line that helps enterprises discover, monitor, and govern AI use across their devices. The role will build backend systems and support a lightweight, native macOS agent that reports AI application use, network destinations, and sensitive-data handling. The engineer will help shape an early-stage product and contribute to the team’s practices for using AI coding agents in enterprise security engineering. AI agents support implementation, testing, and refactoring, while engineers remain responsible for architecture, security decisions, review, and shipped code. The role focuses on scalable Go backend services and distributed microservices for endpoint management, AI security monitoring, and governance. It includes secure communication with large numbers of endpoint agents, multi-tenant architecture, data storage and analytics, service performance and reliability, testing, observability, production troubleshooting, and collaboration across engineering and product teams. The position is hybrid and based in Atlanta, Georgia, or Mountain View, California. Travel is not expected. A bachelor's degree is preferred, or an equivalent combination of education and relevant professional experience. The typical base salary range is USD $141,000–$250,000 per year, with possible eligibility for a corporate bonus program. Omnissa states that it offers employee ownership, health insurance, 401(k) matching, disability insurance, paid time off, growth opportunities, and other benefits. This position is not eligible for employment-based immigration sponsorship.

Requirements

At least 5 years of professional software engineering experience, including substantial backend services and distributed systems work.
Strong hands-on Go programming expertise, including concurrency, goroutines, channels, context management, and performance profiling.
Solid understanding of distributed systems, microservices architecture, asynchronous processing, and fault-tolerant design.
Strong PostgreSQL experience, including schema design, query optimization, indexing, transactions, and performance tuning.
Hands-on experience with Redis or a similar in-memory data store for caching, high-throughput data access, and distributed application patterns.
Experience designing and developing RESTful APIs, gRPC services, and secure client-server communication.
Strong knowledge of data structures, algorithms, networking fundamentals, and concurrent programming.
Experience building scalable, highly available services in containerized environments using Docker and Kubernetes or equivalent orchestration platforms.
Familiarity with event-driven architectures, message queues, or streaming platforms such as Kafka.
Experience with observability, debugging, performance optimization, and production incident troubleshooting.
Understanding of authentication, authorization, encryption, and secure backend development practices.

Nice To Haves

Experience building large-scale SaaS platforms, endpoint management systems, cybersecurity products, or high-volume telemetry processing services.
Hands-on experience with ClickHouse, StarRocks, or similar real-time analytical databases.
Experience designing high-throughput ingestion pipelines, columnar storage architectures, and near-real-time analytics systems.
Knowledge of Apache Kafka, event-stream processing, and distributed messaging patterns.
Experience managing persistent connections with large numbers of distributed clients using gRPC streaming or similar protocols.
Experience with Redis Cluster, PostgreSQL partitioning, replication, connection pooling, and database scalability patterns.
Familiarity with Prometheus, Grafana, OpenTelemetry, Loki, or similar observability technologies.
Experience with Kubernetes, HashiStack (Nomad, Consul, Vault), or other cloud-native infrastructure platforms.
Knowledge of multi-tenant SaaS architectures, tenant-level data isolation, and enterprise security requirements.
Bachelor's degree, or equivalent combination of education and relevant professional experience.

Responsibilities

Design, develop, and maintain scalable, high-performance backend services and APIs using Go.
Build cloud-native distributed microservices for enterprise endpoint management, AI security monitoring, and governance workflows.
Develop secure and efficient communication between endpoint agents and backend services using gRPC, Protocol Buffers, HTTP/2, and REST APIs.
Optimize concurrency, resource utilization, throughput, and latency across distributed services.
Design secure multi-tenant architectures with tenant isolation, authorization, and data protection.
Develop automated unit, integration, performance, and end-to-end tests.
Participate in architecture reviews, code reviews, and technical design discussions.
Contribute to CI/CD automation, infrastructure as code, and reliable production deployments.
Collaborate with endpoint engineering, security, frontend, and product teams to deliver end-to-end capabilities.
Design and optimize PostgreSQL data models, queries, indexing strategies, and database interactions.
Implement caching, distributed coordination, and low-latency data access using Redis or Valkey.
Evaluate and integrate analytical data platforms such as ClickHouse, StarRocks, or Apache Druid for high-volume, low-latency analytical queries.
Design services for high availability, fault tolerance, horizontal scalability, and graceful degradation.
Optimize backend systems for high-concurrency workloads, telemetry ingestion, and low-latency policy operations.
Implement retries, backpressure, rate limiting, idempotency, and failure recovery across distributed services.
Establish observability with metrics, structured logging, distributed tracing, and actionable alerting.
Conduct performance profiling, load testing, capacity planning, and production troubleshooting.
Work with SRE and platform engineering teams to improve reliability, operational efficiency, and deployment automation.