Qualco Technology
forward deployed engineer
Sep 22, 2026 · Qualco Technology
Αττική·Sep 22, 2026
ΑττικήHybridΠληροφορικήPermanentFull Time
JOBILY AI SUMMARY
What you'll do
- Own the deployment lifecycle from client discovery and scoping through POC delivery and production transition
- Design and build production-grade AI agent systems, including RAG pipelines, multi-agent orchestration, and tool engineering
- Select and justify architectures and frameworks, communicating trade-offs to technical and non-technical stakeholders
- Translate discovered use cases into scoped delivery plans and define engagement success criteria with the AI Strategist
- Build client relationships and identify new deployment opportunities throughout each engagement
- Navigate legacy systems, complex data, integration constraints, and compliance requirements to deliver working solutions
- Identify repeatable deployment patterns and escalate them as reusable platform capabilities
- Support systems through pilot evaluation and production, incorporating user feedback
- Work on-site with clients to build end-to-end solutions
- Carry out activities in compliance with regulatory requirements and the Group Anti-Bribery and Corruption Policy
Key requirements
- Production software engineering, AI/ML system development, and machine learning infrastructure
- RAG pipelines, agent and multi-agent architectures, and AI orchestration frameworks
- Enterprise architecture design, system integration, and architecture trade-off analysis
- Client discovery, solution scoping, and proof-of-concept development
- Production deployment and tool and harness engineering
- Regulatory compliance
Benefits
- Benefits include competitive compensation, ticket restaurant card, annual bonus programs, cutting-edge equipment, private health insurance, flexible working options, wellness facilities, and career development through mentoring, coaching, and learning plans.
About the job
The FDE is the person who writes the production code that makes an AI/ML use case real, and who feeds what they learn back into the Core platform so the next deployment starts from a stronger baseline than the last. This is the same field-to-platform feedback loop Palantir calls "gravel road to…

