Supernal
Technology
SeniorAIEngineer(Clients)
Neural analysis suggests this role is
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“Senior AI Engineer (Clients) at Supernal. Skills: AI Engineering, Backend Systems, Agentic AI, LLM Orchestration. Design backend systems. Build backend systems”
Industry & Context.
Debugging complex issues; Diagnose complex issues
What They're Looking For.
Must Have
4+ years software engineering, 4+ years systems engineering, 4+ years automation-focused roles, Hands-on agentic architectures, Hands-on conversational AI systems, Hands-on workflow automation platforms, LLM orchestration experience, Prompt engineering experience, Function calling experience, RAG experience, Build voice systems, Deploy voice systems, Build real-time systems, Deploy real-time systems, API integration patterns, Webhook integration patterns, External services integration patterns, Debugging complex issues, Diagnose distributed systems issues, Diagnose AI pipelines issues, Solid engineering fundamentals, Testing fundamentals, Error handling fundamentals, System design fundamentals, Clean architecture principles, Own delivery outcomes end-to-end, Balance technical execution, Manage client success, Manage timeline management, English communication skills
Nice to Have
Experience building voice systems, Experience deploying voice systems, Experience handling latency, Experience handling streaming, Experience handling failure recovery, Familiarity with integration patterns, Debugging skills, Ability to own delivery outcomes, Explain technical trade-offs clearly, Comfortable in fast-paced environments, Comfortable in ambiguous environments, High ownership, Minimal structure
What You'll Do.
Design backend systems
Build backend systems
Maintain backend systems
Design CRUD applications
Build CRUD applications
Maintain CRUD applications
Develop external APIs
Integrate external APIs
Develop third-party systems
Integrate third-party systems
Build conversational AI systems
Deploy conversational AI systems
Build agentic AI systems
Deploy agentic AI systems
Manage multi-turn dialogue
Own technical delivery
Translate customer requirements
Translate statements of work
Create technical designs
Create implementation plans
Create execution roadmaps
Make architectural decisions
Debug complex production issues
Ensure system reliability
Define engineering best practices
Enforce engineering best practices
Define testing strategies
Enforce testing strategies
Define error handling
Enforce error handling
Enforce observability
Define maintainability standards
Enforce maintainability standards
Collaborate with stakeholders
Manage technical trade-offs
Write automated tests
Maintain automated tests
How You'll Work.
Team & Collaboration
Delivery stakeholders; Product stakeholders
Communication Scope
Explain technical trade-offs
Process & Methodology
System architecture, Planning, Production deployment, Technical designs, Implementation plans, Execution roadmaps, Scope management, Timeline management, Technical trade-offs
Full Job Description
## 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
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