Agentic QA Engineer, Generative AI Systems
Tekfortune Inc.
- Ort
- Dallas, US
- Arbetsplats
- På plats
- Anställningsform
- Heltid
- Lön
- $100k–$118k
- Publicerat
- I dag
- Källa
- DevITJobs
Requirements:
- At least 7 years of experience in software QA/testing, including 2 years working with AI/ML or LLM-based systems and hands-on testing of agentic or multi-agent architectures.
- Strong Python programming skills, including experience building test harnesses, simulators, and fixtures.
- Experience with LLM evaluation methods such as exact or soft match, BLEU/ROUGE, BERTScore, embedding-based semantic similarity, guardrails, and prompt testing.
- Expertise in distributed systems testing, latency profiling, resiliency patterns such as circuit breakers and retries, chaos engineering, and message queues.
- Familiarity with orchestration frameworks such as LangChain, LangGraph, LlamaIndex, DSPy, OpenAI Assistants/Actions, Azure OpenAI orchestration, or similar tools.
- Proficiency with CI/CD tools such as GitHub Actions or Azure DevOps; observability tools such as OpenTelemetry, Prometheus/Grafana, or Datadog; and feature flags or canaries.
- Understanding of privacy, security, and compliance for AI systems, including PII handling, content policies, and model safety.
- Excellent communication and leadership skills, with the ability to work across Operations, Data, and Engineering teams.
- Preferred: Experience with multi-agent simulators, agent graph testing, and tooling latency emulation.
- Preferred: Knowledge of MLOps, including model versioning, datasets, and evaluation pipelines, as well as A/B experimentation for LLMs.
- Preferred: Background in AWS or other cloud environments, serverless, containerization, and event-driven architectures.
- Preferred: Previous ownership of cost, latency, or SLAs for production AI workloads.
Responsibilities:
- Define and lead QA strategy for agentic and multi-agent AI systems across development, staging, and production.
- Mentor QA engineers and establish testing standards, test-harness coding guidelines, and review practices.
- Work with Agentic Operations, Data Science, MLOps, and Platform teams to integrate QA into the software development lifecycle and incident response.
- Test agent orchestration, tool calls, planner-executor loops, and inter-agent coordination, including task decomposition, handoffs, and goal completion.
- Validate state management, context windows, memory and knowledge stores, and prompt or graph correctness under varied conditions.
- Develop scenario-fuzzing tests using adversarial inputs, prompt variations, tool latency spikes, and degraded APIs.
- Build resilience test suites covering chaos experiments, failover, retries and backoff, circuit breakers, and degraded-mode behavior.
- Establish latency SLOs and measure end-to-end response times across LLM calls, tool invocations, queues, and orchestration layers.
- Assess reliability through soak tests, canary verification, and automated rollbacks.
- Define ground-truth and reference pipelines for task accuracy, including exact-match, semantic-similarity, and factuality checks.
- Create macro-validation frameworks to assess outcomes across multi-step agent workflows.
- Instrument and validate guardrails for toxicity, PII, hallucinations, and policy compliance.
- Design load and stress tests for multi-agent graphs, covering concurrency, throughput, queue depth, and backpressure.
- Verify orchestrator behavior, including DAG execution, retries, branching, timeouts, and compensation paths.
- Build reusable test assets such as scenario configurations, synthetic datasets, prompt libraries, agent graph fixtures, and simulators.
- Integrate tests into CI/CD and production monitoring, with pre-merge gates, nightly runs, canaries, and KPI-based alerts.
- Define release criteria and conduct operational-readiness assessments for performance, security, compliance, and cost and latency budgets.
Technologies:
- AI
- AWS
- Azure
- CI/CD
- Cloud
- Datadog
- DevOps
- GitHub
- Grafana
- Support
- LLM
- MLOps
- OpenTelemetry
- Prometheus
- Python
- Security
- Serverless
- Windows
- Agentic AI
More
We are Tekfortune, a consulting firm providing permanent, contract, and project-based staffing services to organizations across a range of industries. We are recruiting a hands-on Agentic QA Engineer to support production-grade generative AI and multi-agent systems in partnership with our Agentic Operations Team. The role focuses on reliability, resilience, accuracy, latency, orchestration, and scale. This is a long-term position based in Dallas, Texas, and is onsite five days per week. The interview process includes one virtual interview and one in-person interview.
last updated 44 week of 2026