Software Test Engineer

BigBear.ai, through its Ask Sage company, provides AI-powered decision intelligence solutions and is hiring a Software Test Engineer to strengthen automated validation across its AI platform. The role focuses on developing scalable smoke, unit, integration, and end-to-end tests; validating backend services, APIs, AI workflows, security-sensitive behavior, and distributed systems; and improving test infrastructure and CI feedback loops.

Responsibilities:

• Develop and maintain smoke tests, unit tests, integration tests, and end-to-end tests across backend and platform workflows
• Validate backend changes for new PRs through automated test coverage, direct API testing, and user-facing workflow verification where appropriate
• Exercise backend behavior through the UI when useful, without owning visual design, frontend UX validation, or manual UI regression testing
• Build regression coverage for edge cases, malformed inputs, authorization boundaries, concurrency issues, failure modes, and other non-happy-path scenarios
• Improve the scalability, determinism, execution performance, maintainability, and diagnostic quality of the test suite
• Strengthen test fixtures, mocks, test data management, failure analysis, and CI feedback loops
• Design end-to-end tests for AI platform workflows while minimizing unnecessary token usage, external provider calls, latency, and test cost
• Apply AI-assisted development and analysis tools to accelerate test design, test generation, triage, and maintenance while preserving reliability, reviewability, performance, and deterministic validation standards
• Validate backend APIs, authentication flows, billing and token behavior, model routing, AI workflow execution, file parsing, MCP/tool execution, and passthrough APIs
• Validate AI platform E2E paths involving prompts, model responses, streaming behavior, tool calls, agents, workflow orchestration, and provider-facing API compatibility
• Validate agentic harnesses, MCP integrations, and workflow automation systems, including concepts common to no-code and low-code workflow builders such as Power Automate, Zapier, Make, n8n, and similar platforms
• Validate security-sensitive product behavior such as user isolation, permission boundaries, validation, sanitization, rate limits, replay prevention, safe error handling, and layered control behavior
• Build and maintain test infrastructure that must scale with a growing platform, expanding product surface area, and active engineering team

Requirements:

• All applicants must currently reside in the United States
• • 8-10 years of experience with software testing
• • Strong software engineering background with deep experience in automated test development
• • Experience testing backend services, APIs, distributed systems, and database-backed applications
• • Experience designing smoke, unit, integration, and end-to-end testing strategies
• • Strong judgment around edge cases, non-happy paths, adversarial inputs, regression risk, and failure isolation
• • Experience improving CI test reliability, execution time, parallelization, test isolation, and failure observability
• • Familiarity with testing Defense in Depth behavior: validating that multiple layers of checks work together, without this being a dedicated DevSec role
• • Strong troubleshooting, analytical, and communication skills
• • Ability to work independently and as part of a team
• • Ability to obtain clearance
• • Experience writing E2E tests for AI platforms, LLM applications, model gateways, agents, MCP tools, or tool-using systems
• • Experience designing AI E2E tests that control token usage, external provider calls, latency, and cost
• • Experience testing workflow automation systems, agentic harnesses, or no-code/low-code automation platforms (e.g., Power Automate, Zapier, Make, n8n)
• • Familiarity with flagship Generative AI provider APIs (Google VertexAI, AWS Bedrock, Microsoft Azure OpenAI) and models (OpenAI GPT, Anthropic Claude, Google Gemini)
• • Experience with CI/CD pipelines (e.g., GitHub Actions), Docker, Kubernetes, and observability/monitoring tooling
• • Experience with PostgreSQL and SQL for validating stored data
• • Knowledge of government compliance frameworks (FedRAMP, NIST AI RMF, CMMC 2.0)