AI Solution Architect

AI Solution Architect<\/b>
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Location: India Remote / Hybrid
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Experience 6\u201310 years of total experience in backend or distributed systems\nengineering, with at least 3\u20134 years of hands\-on, production\-focused experience\nin Generative AI or LLM\-based systems.
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Role Overview
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We are building the next generation of AI\-native products, and we're looking\nfor an AI Solution Architect to be a core part of that foundation.
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This is not a consulting or advisory role. You will own architecture\nend\-to\-end \u2014 designing agentic systems, LLM\-powered platforms, and the\norchestration layers that make them production\-ready at scale. You'll work at\nthe intersection of cutting\-edge AI research and real\-world engineering\nconstraints, shaping how we build and evolve our AI platform.
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If you're excited by the complexity of multi\-agent systems, the challenge of\nmaking LLMs reliable and cost\-efficient in production, and the opportunity to\nset architectural standards in a fast\-moving AI\-native environment \u2014 this role\nis for you.
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Key Responsibilities
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System Architecture
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· <\/span><\/span><\/span>Design\nand own scalable architectures for agentic AI systems and LLM\-powered platforms
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· <\/span><\/span><\/span>Architect\nmulti\-agent systems including planner\-executor patterns, tool\-using agents,\nworkflow automation agents, and dynamic routing and orchestration
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· <\/span><\/span><\/span>Define\nsystem design for RAG pipelines, memory systems (short\-term, long\-term,\nvector\-based), context management, prompt orchestration, and stateful workflows
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Pipeline Engineering
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· <\/span><\/span><\/span>Build\nand optimize AI pipelines for latency, cost (token optimization), scalability,\nand reliability
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· <\/span><\/span><\/span>Design\nintegration patterns with enterprise systems \u2014 APIs, databases, and downstream\nservices
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Reliability & Governance
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· <\/span><\/span><\/span>Establish\nobservability, tracing, and evaluation frameworks for AI systems
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· <\/span><\/span><\/span>Define\nguardrails, safety layers, and failure handling mechanisms
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· <\/span><\/span><\/span>Drive\nbest practices in prompt engineering, system design, and AI architecture
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Collaboration
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· <\/span><\/span><\/span>Work\nclosely with engineering, product, and research teams to translate use cases\ninto production\-grade systems
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· <\/span><\/span><\/span>Contribute\nto platform\-level thinking \u2014 tooling, SDKs, reusable components
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Required Skills & Experience
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Technical Experience
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· <\/span><\/span><\/span>6\u201310\nyears in backend engineering or distributed systems
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· <\/span><\/span><\/span>3\u20134\nyears of hands\-on, production\-grade experience with Generative AI or LLM\-based\nsystems
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· <\/span><\/span><\/span>Demonstrable\nexperience shipping AI systems at scale \u2014 not just prototypes
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Generative AI & LLM Skills
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· <\/span><\/span><\/span>Strong\nunderstanding of LLM architectures, capabilities, and limitations
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· <\/span><\/span><\/span>Hands\-on\nexperience with agentic orchestration frameworks such as LangChain, LangGraph,\nAutoGen, CrewAI, or comparable tools
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· <\/span><\/span><\/span>Experience\nwith RAG architectures, embedding models, and vector databases
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· <\/span><\/span><\/span>Strong\nprompt engineering and context design skills
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Architecture & Systems
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· <\/span><\/span><\/span>Expertise\nin system design, scalability, performance optimization, fault tolerance, and\ncost optimization
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· <\/span><\/span><\/span>Experience\ndesigning backend systems and APIs
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· <\/span><\/span><\/span>Understanding\nof async workflows and event\-driven architectures
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· <\/span><\/span><\/span>Familiarity\nwith cloud platforms (AWS, Azure, or GCP)
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· <\/span><\/span><\/span>Exposure\nto MLOps / LLMOps workflows
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· <\/span><\/span><\/span>Familiarity\nwith observability and tracing tools
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Soft Skills
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· <\/span><\/span><\/span>Ability\nto translate ambiguous business problems into concrete, scalable AI\narchitectures
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· <\/span><\/span><\/span>Comfort\noperating as a senior IC in a fast\-moving, AI\-native environment
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Preferred Qualifications
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· <\/span><\/span><\/span>Experience\nbuilding AI platforms, internal tooling, or developer\-facing SDKs
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· <\/span><\/span><\/span>Understanding\nof AI governance, security, and compliance
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· <\/span><\/span><\/span>Exposure\nto open\-source LLM ecosystems (Llama, Mistral, etc.) in addition to proprietary\nAPIs
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