Technical Architect

AI ArchitectMust Have Technical/Functional SkillsAI / GenAIStrong experience with Generative AI and Agentic AI architecturesHands on knowledge of LLMs, embeddings, RAG pipelines, prompt engineering, and agent frameworksProficiency in Python for AI/ML developmentML & Data EngineeringExperience with ML/DL frameworks such as TensorFlow, PyTorch, scikit learnKnowledge of data engineering, feature engineering, and analytics pipelinesFamiliarity with vector databases, graph databases, and search enginesCloud & PlatformExperience designing AI solutions on cloud platforms (AWS, Azure, or GCP)Strong understanding of cloud native, microservices, and API driven architecturesExposure to observability, monitoring, and logging for AI systemsSecurity & Compliance* Knowledge of data privacy, security best practices, and enterprise compliance standards* Experience designing secure and governed AI solutionsRoles & ResponsibilitiesAI & Solution ArchitectureDefine and own end to end AI architecture for enterprise solutions, from data ingestion to AI driven decisioning and insights.Design AI native platforms where GenAI and ML capabilities are embedded as core services, not bolt ons.Establish modular, reusable, and composable AI components aligned to enterprise architecture standards.Ensure scalability, performance, reliability, and security of AI systems in production.GenAI & Agentic AI* Architect Generative AI solutions, including:o Large Language Models (LLMs)o Retrieval Augmented Generation (RAG)o Multi agent and agent orchestration patterns* Define agent workflows, memory/context handling, tool integration, and decision confidence mechanisms.* Guide responsible selection and usage of cloud based and open source LLMs.Data, ML & MLOpsDesign AI solutions leveraging modern data platforms, feature stores, vector databases, and knowledge graphs.Define MLOps / LLMOps pipelines for training, evaluation, deployment, monitoring, and lifecycle management.Implement mechanisms for model versioning, drift detection, cost optimization, and continuous improvement.Governance, Security & Responsible AIEnsure AI solutions adhere to enterprise security, privacy, and compliance requirements.Embed Responsible AI principles, including explainability, auditability, bias mitigation, and human in the loop controls.Define governance frameworks for model usage, access control, and operational oversight.Technical Leadership & CollaborationAct as technical thought leader for AI initiatives across delivery teams.Collaborate with product owners, UX designers, data engineers, cloud engineers, and DevOps teams.Provide architecture guidance, reviews, and mentorship to senior engineers.Communicate complex AI concepts clearly to technical and non technical stakeholders.EducationBachelor's degreeSalary Range: $170000 - $200000 a year#LI-JH1