AL/ML Technical Architect

Must Have Technical/Functional Skillssignificant depth in AI/ML architecture and solution design on customer-facing programs* Strong hands-on understanding of ML development frameworks and ecosystems(e.g., Python + standard ML/DL libraries like scikit-learn, TensorFlow, PyTorch, HuggingFace)Proven architecture experience for cloud-native AI/ML solutions (AWS/Azure/GCP) and production deploymentsStrong MLOps experience: model lifecycle, governance, monitoring, and production controls.Deep GenAI/LLM architecture experience (RAG patterns, evaluation harnesses, prompt orchestration, guardrails)Graph/Network analytics exposure (Neo4j/TigerGraph/NetworkX/GraphX).Spark/Scala/PySpark at enterprise scale (data processing + ML pipelines)BFSI domain exposure and ability to design within regulated / compliance-heavy environments.Roles & Responsibilities* Architect and drive the design, development, and deployment of scalable ML/AI solutions.* Lead and actively contribute to data science initiatives across the full project lifecycle - fromideation and solution design to hands-on development, deployment, and production support.Define standards, best practices, and governance for AI/ML solutioning and model management.Collaborate with data engineering, MLOps, product, and business teams.Oversee integration of data science models into production systems.Design and implement AI solutions on cloud platforms (AWS/Azure/GCP) and/or on-prem usingopen-source technologies* Evaluate and recommend ML tools, frameworks, and cloud-native services aligned to performance,security, and cost goals.* Ensure architectures address enterprise non-functionals: scalability, resiliency, observability, security,and compliance.* Perform MLOps design and implementation (and lead the team on same if needed) including CI/CD for ML,reproducibility, model registry, monitoring, drift detection, and operational controls* Define standards, best practices, and governance for AI/ML solutioning and model management(validation, documentation, approvals, audits).* Architect solutions leveraging LLMs (including GPT-class models) for enterprise GenAI use cases and designpatterns such as RAG, guardrails, evaluation and safety controls.* Guide data strategy and feature store design; align data engineering and ML engineering for reliable featurepipelines.* Provide architectural direction for big data processing using Spark/PySpark for large-scale feature generationand training workflows.* Partner with stakeholders to identify high-value use cases, shape roadmaps, and translate business requirementsinto robust technical architecture* Present architecture, trade-offs, risk controls, and delivery plans clearly to technical and executive audiences.* Mentor ML engineers, data scientists, and platform teams; establish architectural guardrails, design reviews,and engineering standards.* Open-source contributions or published research.Generic Managerial Skills, If anyA senior AI/ML Architect (15+ years) to perform end-to-end architecture and delivery of scalable, secure,production-grade AI/ML systems for BFSI clients. You will own solution blueprints across the full lifecycle-fromuse-case discovery and architecture to platform selection, MLOps/LLMOps design, deployment, and governance-and mentor cross-functional teams (data scientists, ML engineers, data engineers, and application teams). You will workclosely with stakeholders to identify high-value use cases and ensure seamless integration of models intobusiness applications. Your deep expertise in machine learning, cloud-native architectures, MLOps practices, andfinancial domain knowledge will be essential to influence strategy and deliver transformative business impactSalary Range: $180,000 to $210,000 per year