Senior AI Engineer (Clients)
New
Fully remote role with flexibility to work from anywhere globally.Full-TimeSenior
Salary35 - 50 USD per hour
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Job Details
- Languages
- English
- Experience
- 4+ years of experience
- Required Skills
- Software EngineeringPrompt EngineeringDistributed Systems
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.
Responsibilities
- 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.
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