Senior AI Engineer (Clients) - Supernal

Accountabilities:

• 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.

• 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.

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