QA Test Engineer

Job Summary

• We are a platform team, testing APIs for high performance, automation will be primary focus.
• Hands-on with frameworks/tools such as: UI: Playwright / Cypress / Selenium and API: pytest requests, Postman/Newman, REST Assured
• CI/CD integration: Git, GitHub Actions/Jenkins/GitLab CI, test reporting, gating.
• Test design: equivalence partitioning, boundary testing, risk-based testing, defect triage.
• AI-Specific Testing Competencies (Key)
• LLM/application behavior testing: validating correctness when outputs are probabilistic.
• Evaluation strategies: golden datasets, scoring rubrics, human-in-the-loop reviews.
• Non-determinism handling: statistical assertions, repeated runs, variance thresholds.
• Prompt and regression management: versioning prompts, detecting prompt drift, replay tests.
• RAG testing (if applicable): retrieval quality (recall/precision), grounding checks, citation validation, doc freshness.
• Safety & quality checks: hallucination detection, toxicity/PII leakage checks, policy compliance tests.
• Data & Observability:
• Ability to create and maintain test datasets (structured unstructured), including edge cases.
• Familiarity with telemetry for AI systems:
• Logging prompts/outputs safely, traceability, correlation IDs
• Tools like OpenTelemetry, ELK/Splunk, Datadog/Grafana (any equivalent)
• Performance & Reliability Testing (AI-Aware)
• Load/performance testing for inference endpoints (latency, throughput, concurrency).
• Cost-aware testing (token usage, rate limits, fallbacks).
• Resilience tests: retries, circuit breakers, model timeouts, degraded-mode behavior.
  

Qualifications

• Bachelor's in Computer Science, Engineering, Data/Information Systems, or equivalent practical experience.
• 3 years in QA automation or SDET-type work (adjust by level); 1 year exposure to AI/LLM or ML-driven features is a plus.
• Nice-to-Have Domain Knowledge
• Familiarity with NLP concepts (embeddings, context windows, temperature/top-p).
• Experience with AI tooling: LangChain/LlamaIndex, evaluation tools, model gateways.
• Knowledge of regulatory/security needs relevant to the telecom domain.
• Strong communication-able to explain AI quality issues clearly to product and engineering.
• Comfortable partnering with data science/ML engineers and backend teams.
• Ownership mindset: building reusable test harnesses, improving quality metrics, preventing regressions.
• Strong test automation in Python and/or Java/TypeScript.
• Strong communication and analytical skills.
• Understanding of data privacy constraints (masking/redaction) and secure test data practices.
• API / Microservices / Cloud
• Comfortable testing distributed systems: microservices, async workflows, queues/events.
• Basic cloud proficiency (AWS/Azure/GCP) and containerization (Docker, optional Kubernetes).
  
  

Benefits

Healthcare Insurance: Synectics offers eligible employees and their dependents healthcare coverage through BlueCross BlueShield of Illinois. Eligibility begins on the 1st day of the calendar month following 60 days of continuous full time employment with Synectics. Premiums are subsidized by Synectics.

Dental Insurance: Synectics offers eligible employees and their dependents a dental plan through MetLife. Eligibility begins on the 1st day of the calendar month following 60 days of continuous full time employment with Synectics.

Vision Insurance: Synectics offers eligible employees vision insurance through VSP. Eligibility begins on the 1st day of the calendar month following 60 days of continuous full time employment with Synectics.

401(k) Plan: The Synectics Inc. Investment Savings Retirement Plan. Synectics offers all employees who are 21 years of age or older the opportunity to invest in the 401(k) Plan on the first of the month following at least 1 calendar year after employment begins.

Synectics is an equal opportunity employer.