You will be responsible for building, testing, and stress-testing agentic systems while acting as the primary bridge between engineering and adopting teams. This involves running evaluation pipelines, gathering user feedback, and defining actionable requirements to improve the platform roadmap.
About Us
Foundever™ is a global leader in the customer experience (CX) industry. With 150,000 associates across the globe, we are the team behind the best experiences for more than 750 of the world's leading and digital-first brands. Our innovative CX solutions, technology, and expertise are designed to support operational needs for our clients and deliver seamless, AI-driven experiences in the moments that matter.
As AI becomes increasingly agentic and autonomous, we are building a platform to orchestrate intelligent workflows that automate complex business processes at scale.
About the role
We are looking for an Agentic Systems Builder & QA Engineer to sit at the intersection of building, testing, and adoption of our agentic systems framework. You will be the first user of the tools we build — stress-testing them, running evaluations, identifying gaps, and feeding insights back to the engineering team.
Beyond QA, you will play a key role in enabling other teams to build with our framework: onboarding them, understanding their use cases, translating their needs into actionable specs, and running discovery to inform the platform roadmap. You will combine hands-on building and testing with product-minded thinking — ensuring that what we ship is not only technically sound but genuinely useful for the teams adopting it.
This role is ideal for someone who enjoys working across boundaries: part builder, part tester, part enabler — with a strong sense for what makes tools intuitive, reliable, and ready for real-world use.
Key responsibilities
Building & Testing
Be the primary hands-on tester of the agentic systems framework — building agents using our tools, identifying bugs, edge cases, and usability issues before other teams encounter them
Run end-to-end evaluations of agentic systems: execute evaluation pipelines, create and curate datasets, analyze results, and report on agent quality and reliability
Build and configure agentic workflows using the framework's interfaces — system prompts, model selection, tool integrations — validating that the developer experience works as intended
Define and execute QA processes for new framework features, integrations, and releases
Adoption & Enablement
Support other technical teams in building agentic systems with our tools — onboarding, troubleshooting, and sharing best practices
Act as the bridge between adopting teams and the engineering team: gather feedback, identify friction points, and advocate for improvements
Create documentation, guides, and examples that help teams get started and build effectively
Discovery & Product
Run discovery with internal teams to understand their use cases, pain points, and requirements for agentic systems
Translate user needs into clear specs and requirements that the engineering team can act on
Help prioritize framework improvements based on real adoption feedback and observed usage patterns
Contribute to roadmap discussions with a grounded perspective on what teams actually need
Evaluation & Quality
Execute and refine evaluation workflows — running experiments, comparing agent configurations, and reporting on metrics
Help define what "good" looks like for agent behavior in different use cases
Flag quality issues, regressions, and drift in deployed agentic systems
Skills / Abilities / Knowledge
Experience
3+ years in a role combining development, QA, testing, or technical product work
Experience building or configuring AI/ML-powered systems or applications
Experience working directly with end users or internal teams to gather requirements and feedback
Some exposure to product management practices: discovery, spec writing, prioritization
Required
Comfort working with APIs, configuration interfaces, and developer tooling
Understanding of LLMs and how they are integrated into applications (prompting, tool calling, structured outputs)
Strong analytical and communication skills — able to clearly articulate issues, feedback, and requirements
Detail-oriented with a quality-first mindset
Comfortable in Agile, fast-paced environments with evolving scope
Nice to have
Experience with agentic systems or agent orchestration frameworks (LangGraph, LangChain, or similar)
Experience with observability or evaluation tooling (LangFuse or similar)
Experience with MCP Servers/Clients
Background in QA engineering or test automation
Experience with testing methodologies — manual and/or automated, ideally for AI or non-deterministic systems
Experience in a product management or technical product owner role
Development skills in Python
Familiarity with vector databases, RAG pipelines, or NLP
Experience writing technical documentation or developer guides
Education
Bachelor's degree or higher in Computer Science, Engineering, or a related field — or equivalent practical experience.
Languages
Excellent written and conversational English (C1 minimum)
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