Quality Engineer (AI Focused)

About the job:

This role will own the end-to-end quality strategy for AI Marketplace solutions, including QE agent development, AI validation, workflow orchestration, and platform integration. Define standards for AI testing, observability, security, and performance while enabling rapid adoption of reusable QE agents across projects. Provide technical leadership and mentorship to engineering teams in building and deploying agentic solutions.

What you will do at Sogeti:

Agentic AI Architecture: Understanding AI agents, multi-agent workflows, MCP (Model Context Protocol), orchestration frameworks, tool calling, memory management, RAG patterns, and agent lifecycle management.

AI/LLM Validation & Assurance: Ability to define and implement testing strategies for AI systems including hallucination detection, response quality evaluation, guardrail testing, prompt validation, grounding verification, and reliability testing.

QE Automation Engineering: Strong hands-on experience with Playwright, Selenium, API automation, test frameworks, CI/CD integration, test data management, and automation architecture.

Agent Development & Customization: Ability to configure, extend, and customize agents for project-specific workflows, enterprise tools, APIs, business rules, and testing use cases.

AI Observability & Monitoring: Knowledge of agent telemetry, trace analysis, execution monitoring, prompt/response tracking, drift detection, performance analytics, and operational dashboards.

Cloud & Platform Engineering: Working knowledge of Azure AI, AWS Bedrock, OpenAI, Databricks, Kubernetes, containers, APIs, security integrations, and enterprise deployment patterns.

Data & API Engineering: Strong understanding of API contracts, service orchestration, structured/unstructured data, vector databases, embeddings, and data validation techniques.

Responsible AI & Governance: Understanding AI agents, multi-agent workflows, MCP (Model Context Protocol), orchestration frameworks, tool calling, memory management, RAG patterns, and agent lifecycle management.

Performance & Scalability Testing: Ability to validate agent response latency, concurrency, token consumption, workflow scalability, resiliency, and failover behavior.

Solution Architecture & Consulting: Capability to translate business use cases into agentic solutions, define reusable marketplace assets, establish standards, and mentor engineering teams.

What you will bring:

• Playwright (must have) or modern automation framework

• Agentic AI / LLM fundamentals

• API testing and integration

• AI testing and validation

• Azure AI/OpenAI ecosystem

• Strong QE architecture background

• LangChain / LangGraph

• AutoGen / CrewAI / Semantic Kernel

• Vector databases

• MCP-based architectures

• Kubernetes & containers

• Prompt engineering

About Sogeti

Part of the Capgemini Group, Sogeti makes business value through technology for organizations that need to implement innovation at speed and want a local partner with global scale. With a hands-on culture and close proximity to its clients, Sogeti implements solutions that will help organizations work faster, better, and smarter. By combining its agility and speed of implementation through a DevOps approach, Sogeti delivers innovative solutions in quality engineering, cloud and application development, all driven by AI, data and automation.

Sogeti is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.