Qureos Mentor

Ai India Innovations

We&rsquo;re Hiring: AI Tech Lead (Real-Time AI &amp; GenAI Systems)We are looking to hire a strong AI Tech Lead who can architect and guide the implementation of real-time AI systems across voice automation, LLM pipelines, and knowledge-enhanced applications.This role demands deep architectural judgment, hands-on expertise with LLMs and GenAI, and the ability to define best practices, performance benchmarks, and scalable system designs for low-latency, production-grade AI products.Role OverviewAs an AI Tech Lead, you will lead the design and development of distributed, provider-agnostic AI architectures involving multi-provider LLMs, speech pipelines (STT/TTS), and AI microservices. You will be responsible for ensuring low latency, high reliability, scalability, and cost efficiency across real-time AI systems.You will also set technical standards, guide engineers, and make high-impact architectural decisions for enterprise and customer-facing AI products.Key ResponsibilitiesAI Architecture &amp; Systems Design<ul><li>Architect and lead development of real-time AI systems including:</li><li>Multi-provider LLM pipelines</li><li>Speech-to-text (STT) and text-to-speech (TTS) chains</li><li>Distributed AI microservices</li><li>Ensure low speech-to-speech latency, resilient failover, load balancing, and horizontal scaling</li><li>Design provider-agnostic architectures with intelligent routing and fallback strategies</li><li>Optimize inference paths for performance and cost efficiency</li></ul>GenAI Best Practices &amp; Governance<ul><li>Define architectural &ldquo;dos and don&rsquo;ts&rdquo; for GenAI systems:</li><li>Prompt design and safety patterns</li><li>Context shaping and window optimization</li><li>Caching and fallback logic</li><li>Real-time agent orchestration</li><li>Lead model governance and evaluation frameworks:</li><li>Benchmarking multiple LLM providers</li><li>Routing logic based on latency, quality, and cost</li><li>Token efficiency and context management</li><li>Establish KPIs for:</li><li>LLM quality and grounding accuracy</li><li>Latency and reliability</li><li>Cost control and system stability</li></ul>Knowledge &amp; RAG Architecture<ul><li>Own end-to-end RAG and knowledge integration architecture</li><li>Design and optimize:</li><li>Vector databases and retrieval strategies</li><li>Chunking and embedding policies</li><li>Context enhancement and hybrid grounding approaches</li><li>Function calling, tool use, and emerging knowledge-graph integrations</li><li>Ensure retrieval quality supports accurate, safe, and domain-grounded responses</li></ul>Security &amp; Data Handling<ul><li>Ensure secure handling of voice and transcript data</li><li>Apply basic PII-safe practices and data isolation</li><li>Support retention, deletion, and multi-tenant data controls</li></ul>Technical Leadership<ul><li>Provide technical guidance and mentorship to AI engineers</li><li>Define performance benchmarks, design standards, and review practices</li><li>Stay ahead of new LLM capabilities, voice AI trends, and GenAI tooling</li></ul>Required Skills &amp; Experience<ul><li>Strong experience designing and building production-grade AI systems</li><li>Deep hands-on expertise with LLMs, RAG, and GenAI architectures</li><li>Experience with real-time or low-latency systems (voice AI preferred)</li><li>Strong understanding of distributed systems, microservices, and scaling patterns</li><li>Experience working with multiple LLM providers and routing strategies</li><li>Ability to balance quality, latency, reliability, and cost</li><li>Strong architectural thinking and decision-making skills</li></ul>Nice to Have<ul><li>Experience with voice automation platforms and conversational AI</li><li>Exposure to function calling, tool-using agents, and knowledge graphs</li><li>Prior experience defining AI governance or platform standards</li><li>Experience in multi-tenant SaaS AI platforms</li></ul>What You&rsquo;ll Get<ul><li>Ownership of core AI architecture decisions</li><li>Opportunity to build and scale real-time AI systems used in production</li><li>Work on cutting-edge voice AI, LLM, and knowledge-grounded applications</li><li>Influence long-term AI platform strategy and technical direction</li><li>Collaborate with senior engineers, product leaders, and founders</li></ul>Role: AI Tech Lead Location: Pune / Hybrid (as applicable) Experience Level: Senior / LeadJob Type: Contractual / Temporary Contract length: 6 monthsPay: ₹213,343.82 - ₹303,019.68 per monthWork Location: In person

AI / ML Lead

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Ai India Innovations

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AI / ML Lead