Senior AI Engineer (Clients) - Supernal

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI Engineer (Clients) – Supernal based in Poland.

This role sits at the intersection of advanced software engineering, AI systems design, and real-world client delivery, where you will build production-grade AI employees deployed in live business environments. You will design and ship the core systems powering agentic workflows, conversational AI, and external integrations that enable intelligent automation at scale. The work goes far beyond experimentation — you will be responsible for building reliable, latency-aware, and fault-tolerant systems that handle real users and real business constraints. You will also act as a technical owner for client implementations, translating requirements into robust engineering solutions. Operating in a fast-paced, startup-like environment, you will balance hands-on coding with architectural decision-making and delivery accountability. Your impact will be directly visible in production systems used by customers to run critical operations. This is a highly ownership-driven role where engineering excellence and delivery outcomes go hand in hand.

• Design, build, and maintain production-grade backend systems, including services, data models, and CRUD applications supporting AI-driven workflows.
• Develop and integrate external APIs, webhooks, and third-party systems to enable secure and reliable AI agent actions.
• Build and deploy conversational and agentic AI systems, including multi-turn dialogue management, state handling, and tool use orchestration.
• Own end-to-end technical delivery for client implementations, from system architecture and planning through to production deployment.
• Translate customer requirements and statements of work into clear technical designs, implementation plans, and execution roadmaps.
• Make architectural decisions across system design, LLM orchestration, RAG pipelines, integrations, and workflow decomposition.
• Debug complex production issues across distributed systems, AI agents, prompts, and external dependencies while ensuring system reliability.
• Define and enforce engineering best practices, including testing strategies, error handling, observability, and maintainability standards.
• Collaborate closely with delivery and product stakeholders to manage scope, timelines, and technical trade-offs.
• Write and maintain automated tests (unit, integration, and end-to-end) to ensure system stability and production readiness.

Requirements:

• 4+ years of experience in software engineering, systems engineering, or automation-focused roles delivering production-grade systems.
• Strong hands-on experience building agentic architectures, conversational AI systems, or workflow automation platforms.
• Proven experience working with LLM orchestration, prompt engineering, function calling, and retrieval-augmented generation (RAG).
• Experience building and deploying voice or real-time systems, including handling latency, streaming, and failure recovery scenarios.
• Familiarity with integration patterns involving APIs, webhooks, and external services in production environments.
• Strong debugging skills with the ability to diagnose complex issues across distributed systems and AI pipelines.
• Solid engineering fundamentals, including testing, error handling, system design, and clean architecture principles.
• Ability to own delivery outcomes end-to-end, balancing technical execution with client success and timeline management.
• Strong communication skills in English, with the ability to explain technical trade-offs clearly to both technical and non-technical stakeholders.
• Comfortable working in fast-paced, ambiguous environments with high ownership and minimal structure.

Benefits:

• Competitive hourly compensation ranging from $35–50/hour depending on experience.
• Fully remote role with flexibility to work from anywhere globally.
• Opportunity to work on cutting-edge AI agent and conversational system deployments in real-world production environments.
• High-impact engineering role with strong ownership over client delivery and technical architecture decisions.
• Exposure to advanced AI workflows, LLM systems, and agentic infrastructure at scale.
• Startup-like environment with fast iteration cycles and high technical autonomy.
• Opportunity to shape engineering best practices and influence production-grade AI system design.