Senior / Staff Software Engineer – Integration Team

Stellar Cyber

. Own one or more integration domains end-to-end, including roadmap, architecture decisions, trade-offs, and delivery .

Posted 10/28/2026full-timeRemote • United StatesSenior💰 $160,000 - $245,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in backend software development with a focus on integration, data parsing, and log processing. Proficient in utilizing AI tools for automation and enhancing system performance while mentoring junior engineers and collaborating with cross-functional teams.

Highest-signal resume keywords

Backend Software DevelopmentAPI Design and IntegrationAI Tool UtilizationMicroservice ArchitectureData Normalization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonGoJavaC++RESTGraphQLJSONXMLData ParsingSchema Design

Soft Skills

Problem-SolvingClear CommunicationMentoring

Tools & Technologies

AWSAzureGCPDockerKubernetesKafkaRabbitMQCeleryAirflowAI Services

Industry Keywords

CybersecuritySOAREDRSIEMXDRCloud SecurityReal-Time PipelinesEvent-Driven ArchitectureProduction MicroservicesLog Analysis

Tech Stack

Tools & technologies

AirflowAWSAzureCloudCyber SecurityDistributed SystemsDockerFirewallsGoogle Cloud PlatformGraphQLJavaKafkaKubernetesMicroservicesPythonRabbitMQSparkC++Go

About the role

Key responsibilities & impact

Own one or more integration domains end-to-end, including roadmap, architecture decisions, trade-offs, and delivery
Identify problems, scope solutions, and drive projects to completion
Own and evolve shared integration frameworks such as the parser framework
Identify reusable patterns and design primitives for other engineers
Improve performance on hot paths and raise reliability and testability standards
Make design decisions involving schema mapping, normalization trade-offs, malformed data, generalization, special-casing, and framework evolution
Partner with detection and data teams to ensure ingested data supports downstream use cases
Mentor junior engineers through design discussions and code reviews
Use LLM-based coding assistants, AI-driven testing, and automated code review
Use LLMs to analyze log samples, propose parsing rules, and accelerate integrations
Automate builds, deployments, monitoring, incident triage, parser regression testing, and schema diffing with AI and scripting
Champion AI adoption, build internal tooling, and measure efficiency gains
Deliver microservice-based integrations using REST, GraphQL, streaming APIs, MCP, and LLM-powered automation
Design, develop, and maintain parsing and normalization components for security data from hundreds of sources

Requirements

What you’ll need

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
5+ years of backend software development experience, including integration, data parsing, or log processing work
1+ years as a technical lead or proven experience in taking full ownership of a project
Strong proficiency in at least one general-purpose programming language, such as Python, Go, Java, or C++
Track record of writing production-quality code
Experience with API design and integration, including REST, GraphQL, streaming, OAuth, API keys, and rate limiting
Understanding of JSON, XML, CSV, syslog, key-value, unstructured text, regular expressions, data normalization, and schema design
Demonstrated regular production use of AI tools such as Copilot, Cursor, Claude, or ChatGPT
Judgment to assess when AI output requires human expertise
Strong problem-solving skills
Clear communication with engineers and non-technical stakeholders
Preferred: cybersecurity domain experience, including SOAR, EDR, SIEM, XDR, firewalls, IDS/IPS, or cloud security services
Preferred: experience building and operating production microservices
Preferred: large-scale data processing, real-time pipelines, or event-driven architectures such as Kafka or Spark
Preferred: distributed systems, message queues such as Kafka or RabbitMQ, or orchestration frameworks such as Celery or Airflow
Preferred: AWS, Azure, GCP, CloudWatch, Azure Monitor, Cloud Logging, Docker, Kubernetes, or Helm
Preferred: AI service integration, LLM APIs, embedding services, MCP, function calling, agent orchestration frameworks, or systems incorporating LLMs or AI services
Preferred: using LLMs for log analysis, parser generation, schema inference, or AI-based data engineering tooling

Benefits

Comp & perks

Pre-IPO Stock Options (equity opportunity)
Medical, Dental & Vision care
Life Insurance
401(k)
Employee Assistance Program
Employee Discount Program
Paid time off
Referral Program
Rewards and Recognition Program
Competitive salary
Ample career growth opportunities