We are looking for a Lead AI Engineer with strong hands-on experience in GenAI, LLM-powered agents, agentic workflows, and test automation engineering to build reusable AI-driven testing solutions across enterprise microservices.

Must-Have Skills:

GenAI / Agentic AI:

Hands-on experience building LLM-powered agents / Agentic AI.
Tool-using and multi-step agent workflows.
Prompt engineering & structured JSON outputs.
LLM evaluation, guardrails & hallucination reduction.
AI agents for test generation, requirements validation, failure analysis & reporting.

GitHub / GitHub Copilot:

Strong hands-on GitHub Copilot (GHCP) experience.
GitHub Actions & CI/CD.
Reusable workflows & composite actions.
PR checks, branch protection, CODEOWNERS & templates.
GitHub APIs / Webhooks.

Test Automation:

Advanced Karate – API testing, contract testing, mocks & data-driven testing.
Advanced Playwright – UI automation, selectors, parallel execution & trace/video artifacts.
API, UI, integration & contract testing.
Happy path, negative, edge & boundary testing.
Test data setup/teardown & test isolation.

AI-Powered Quality & Reporting:

Aggregate test results across multiple microservices & CI pipelines.
Failure clustering & trend analysis.
Log/metrics/trace correlation.
GenAI-driven release readiness summaries.
“What changed?” insights using commit/PR correlation.
Automated dashboards, CI artifacts & PR reporting.

Quality Gates & Requirements Validation:

Build AI agents to review user stories and requirements.
Acceptance criteria completeness.
Missing edge cases & ambiguity detection.
Test data & environment dependency validation.
Performance, security & observability requirements.
GitHub workflow / PR quality gates.

Ideal Candidate:
Someone who combines AI/LLM engineering + Agentic AI + Test Automation + GitHub/GitHub Copilot and can design scalable solutions that can be adopted across multiple engineering teams.

Saggi Solutions

Lead AI Engineer – Agentic Test Automation

About the Job