appiness Interactive
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Jobs at appiness Interactive
Position Overview:
The AI Tech Lead will architect and guide the implementation of real-time AI systems across voice automation, LLM pipelines, and knowledge-enhanced applications. The role requires strong architectural judgment, hands-on expertise in AI/LLM systems, and the ability to define high-performance, scalable best practices.
Key Responsibilities:
• Architect and guide implementation of real-time AI systems across voice automation, LLM pipelines, and knowledge-enhanced applications
• Design and develop distributed, provider-agnostic AI architectures with performance guarantees including low latency, resilient failover, distributed scaling, and cost-efficiency
• Define architectural best practices for GenAI systems including prompt design, context shaping, fallback logic, caching, and real-time agent orchestration
• Lead AI model governance including evaluation and selection frameworks for multiple LLM providers, routing logic, benchmarking, and cost management
• Establish and monitor KPIs for LLM quality, latency, reliability, grounding accuracy, and system stability
• Ensure data security practices for handling of voice and transcript data, applying PII-safe methods, and supporting multi-tenant data isolation
• Own knowledge integration and RAG architecture including vector databases, retrieval strategies, chunking policies, and hybrid grounding methods
• Continuously evaluate new model capabilities and AI technology trends
Required Skills:
• Architectural judgment and hands-on expertise in AI and LLM systems • Experience designing scalable and low-latency AI architectures
• Knowledge of multi-provider LLM integration and orchestration
• Understanding of distributed systems, microservices, and load balancing
• Strong grounding in AI model governance and benchmarking
• Awareness of data security and privacy best practices
• Experience with retrieval-augmented generation (RAG) and vector databases
Preferred (Bonus) Skills:
• Experience with function-calling and knowledge graphs
• Familiarity with hybrid grounding and retrieval enhancement strategies • Experience with voice automation systems (STT/TTS pipelines). give me in a proper formate
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