Applied AI Engineer (LLM & Voice)

Applied AI Engineer (LLM & Voice)

About Us

GönderAL is a financial technology company focused on building secure and scalable digital payment platforms. We design systems that support real-time transactions, robust infrastructure, and user-friendly interfaces tailored for modern financial operations. We operate in a dynamic, collaborative environment focused on secure, reliable, and customer-centered financial services.

For us, impact is the driver of our work. We value ownership, practical problem-solving, and teamwork to deliver meaningful solutions for our customers and partners.

The Mission

We’re looking for an Applied AI Engineer to build intelligent, agent-driven experiences that let users interact with complex systems through natural language, voice, and structured workflows. In this role, you will design and deploy production-grade AI agents that interpret user intent, reason over domain data, and execute actions safely and reliably.

You’ll work at the intersection of LLMs, voice interfaces, orchestration, retrieval, and backend systems, building robust Voice-to-Action and conversational AI pipelines that combine model reasoning with deterministic business logic. The ideal candidate is excited about creating domain-constrained, high-reliability AI systems with strong guardrails, predictable behavior, and seamless integration with APIs and tools.

What You’ll Do

• Design and deploy LLM-powered agents that support text and voice interactions
• Build Voice-to-Action pipelines that combine speech recognition, LLM reasoning, and automated task execution
• Translate user intent into structured financial actions and workflow execution
• Implement tool-using agents that interact with internal APIs and external tools/services
• Develop agent orchestration, memory, dialogue management, and context systems for reliable multi-step workflows
• Build retrieval-based and knowledge-grounded pipelines for domain-specific assistants
• Design hybrid AI architectures that combine LLM reasoning with rule-based logic for safe, explainable, and predictable behavior
• Create guardrails and control layers to ensure safe, accurate, and domain-restricted outputs
• Evaluate and integrate state-of-the-art LLM models, multimodal systems, and agent architectures into production
• Collaborate with product and engineering teams to deliver scalable AI systems that are reliable in real-world environments

What We’re Looking For

• Experience building LLM-powered agents or applied AI systems in production
• Strong backend engineering skills in Python
• Experience with tool calling, agent orchestration, retrieval systems, and API integrations
• Solid understanding of conversational AI architecture and structured interaction design
• Experience building reliable AI systems with strong guardrails, validation, and hallucination mitigation
• Familiarity with prompt engineering and instruction design for domain-specific workflows
• Ability to combine probabilistic AI systems with deterministic business logic

Nice to Have

• Experience with voice interfaces, including speech-to-text and text-to-speech systems
• Experience building multimodal agents that work across voice, text, and structured inputs
• Experience with domain-specific AI assistants or topic-restricted chat systems
• Experience designing Voice-to-Action workflows
• Familiarity with dialogue management systems and conversational state handling