[Remote] AI Architect (Growth Lead)

Note: The job is a remote job and is open to candidates in USA. Tredence Inc. is seeking a hands-on AI Growth Leader with deep technical expertise in designing, building, and scaling GenAI and agentic AI systems. This role focuses on architecture, engineering execution, and innovation, overseeing the end-to-end lifecycle of intelligent systems while collaborating with business and client stakeholders.ResponsibilitiesDesign and implement end-to-end GenAI systems, including:Multi-agent architectures (planner-executor models, autonomous agents)RAG pipelines and knowledge-grounded AI systemsTool-augmented LLM workflows (function calling, API orchestration)Build production-ready AI solutions, not just prototypes, ensuring scalability, reliability, and observabilityDevelop reusable frameworks, accelerators, and reference architectures for enterprise AI adoptionArchitect and deploy agentic AI solutions with:Memory, reasoning, task decomposition, and self-improvement loopsMulti-agent collaboration and orchestration patternsWorkflow automation using LLM-driven decision enginesExperiment with advanced paradigms such as:Reflection and planning agentsRetrieval + reasoning hybrid systemsAutonomous pipelines for analytics and operationsWork hands-on with:Frameworks: LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAIModels: OpenAI, Claude, open-source LLMs (Llama, Mistral, etc.)Vector DBs: Pinecone, Weaviate, FAISS, Azure AI SearchBuild and optimize:Prompt engineering strategiesFine-tuning and adaptation (LoRA, PEFT where applicable)Latency, cost, and inference optimizationImplement evaluation pipelines (hallucination detection, grounding accuracy, guardrails)Architect and deploy solutions on:Azure OpenAI, AWS Bedrock, Google Vertex AIBuild scalable pipelines using:Kubernetes, serverless architectures, API gatewaysData pipelines (Airflow, Kubeflow, Spark where needed)Ensure MLOps / LLMOps practices, including:CI/CD for AI systemsModel/version lifecycle managementMonitoring and feedback loopsBuild POCs, MVPs, and experimental systems rapidly to validate new ideasTranslate ambiguous business problems into working AI solutions quicklyStay at the cutting edge of:Multimodal AIAI agents and orchestration frameworksEdge AI and lightweight deploymentsSkills7 - 12 Years of experience in AI architecture and developmentDeep technical expertise in designing, building, and scaling GenAI and agentic AI systemsExperience with multi-agent systems and LLM orchestrationHands-on experience in prototyping and proof-of-concepts to production-grade deploymentsAbility to design and implement end-to-end GenAI systemsExperience with multi-agent architectures (planner-executor models, autonomous agents)Knowledge of RAG pipelines and knowledge-grounded AI systemsExperience with tool-augmented LLM workflows (function calling, API orchestration)Ability to build production-ready AI solutions ensuring scalability, reliability, and observabilityExperience in developing reusable frameworks, accelerators, and reference architectures for enterprise AI adoptionExperience in architecting and deploying agentic AI solutions with memory, reasoning, task decomposition, and self-improvement loopsKnowledge of multi-agent collaboration and orchestration patternsExperience in workflow automation using LLM-driven decision enginesAbility to experiment with advanced paradigms such as reflection and planning agents, retrieval + reasoning hybrid systems, and autonomous pipelines for analytics and operationsHands-on experience with frameworks such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAIExperience with models like OpenAI, Claude, and open-source LLMs (Llama, Mistral, etc.)Knowledge of vector databases such as Pinecone, Weaviate, FAISS, Azure AI SearchAbility to build and optimize prompt engineering strategiesExperience in fine-tuning and adaptation (LoRA, PEFT where applicable)Knowledge of latency, cost, and inference optimizationExperience in implementing evaluation pipelines (hallucination detection, grounding accuracy, guardrails)Experience in architecting and deploying solutions on Azure OpenAI, AWS Bedrock, Google Vertex AIAbility to build scalable pipelines using Kubernetes, serverless architectures, and API gatewaysExperience with data pipelines (Airflow, Kubeflow, Spark where needed)Knowledge of MLOps / LLMOps practices, including CI/CD for AI systems, model/version lifecycle management, and monitoring and feedback loopsAbility to build POCs, MVPs, and experimental systems rapidly to validate new ideasAbility to translate ambiguous business problems into working AI solutions quicklyKnowledge of cutting-edge technologies in multimodal AI, AI agents and orchestration frameworks, and edge AI and lightweight deploymentsCompany OverviewTredence is a global data science solutions provider focused on solving the last mile problem in AI. It was founded in 2013, and is headquartered in San Jose, California, USA, with a workforce of 1001-5000 employees. Its website is http://tredence.com.Company H1B SponsorshipTredence Inc. has a track record of offering H1B sponsorships, with 12 in 2026, 143 in 2025, 103 in 2024, 103 in 2023, 74 in 2022, 69 in 2021, 75 in 2020. Please note that this does not guarantee sponsorship for this specific role.