Forward Deployed Engineer

Excerpt from the original posting

We are QUALCO, the technology arm of Qualco Group, with over 25 years of experience in delivering innovative solutions to the financial sector. We serve clients in over 30 countries, helping banks and other financial institutions manage credit and loans effectively while ensuring full regulatory compliance. Our advanced software leverages analytics, artificial intelligence, and digital technologies to support every stage of the credit and lending lifecycle, remaining at the forefront of fintech innovation.

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 paved highway".
How your time breaks down: 
- Full-stack AI/agent development — writing production code, building integrations;
- Enterprise architecture design — deciding how the solution fits the client's real systems and constraints;
- Strategic client discovery — understanding the client's workflows well enough to know what's actually worth building.
What you'll actually do: 
- Own the full lifecycle of a deployment: customer discovery, scoping and solution architecture, POC sprint, and the transition from POC to production;
- Design and build production-grade AI agent systems — RAG pipelines, agent and multi-agent orchestration, tool/harness engineering — against real client data and infrastructure, not synthetic demos;
- Select and justify the right architecture and framework for each use case, with clear trade-offs communicated to both technical and non-technical stakeholders;
- Partner with the AI Strategist to translate discovered use cases into a scoped delivery plan, and jointly define what "resolved" means for each engagement;
- Build long-term relationships with the client and proactively surface new deployment opportunities across the engagement — this overlaps deliberately with the AI Strategist's remit; both roles are expected to keep finding what's next;
- Navigate real enterprise constraints — legacy systems, messy data, integration limits, compliance requirements — and still ship something that works;
- Identify and codify repeatable deployment patterns, escalating them to the AI Studio Core team as candidates for reusable platform capability rather than solving the same problem from scratch each time;
- Support the system through pilot evaluat…

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