Senior Enterprise Architect with AI/ML

Position: Senior Enterprise Architect with AI/MLLocation: Reston, VA ONLY (Three Days Onsite position)Duration: 12+ Months Role Summary We are seeking a senior Enterprise Architect to lead the design of cloud-native MLOps and data platforms on AWS. This role is focused on enterprise-scale architecture, platform design, and governance of the ML lifecycle"”not model development or pipeline implementation. The ideal candidate brings deep expertise in AWS cloud architecture and MLOps platform design, with the ability to define reference architectures, standards, and scalable patterns that enable multiple teams to build and operate machine learning solutions in a secure, compliant, and repeatable manner.Key Responsibilities Define and lead enterprise MLOps architecture across the full ML lifecycle:data ingestion, feature engineering, training, validation, deployment, monitoring, and retrainingDesign cloud-native reference architectures on AWS for ML platforms and data-driven applicationsEstablish standards and governance for:model lifecycle management (versioning, lineage, approvals)reproducibility and environment standardizationresponsible AI and auditabilityArchitect scalable ML inference solutions using microservices and event-driven patterns (batch and real-time)Define CI/CD patterns for ML and integrate with enterprise DevOps toolingPartner with business and engineering teams as a trusted advisor to translate requirements into scalable architecturesLead cloud adoption and modernization strategies, including AWS landing zones and multi-account designCollaborate with Security, Risk, and Compliance teams to ensure secure-by-design and compliant architecturesProduce architecture artifacts (reference architectures, diagrams, roadmaps)Required Experience12+ years of experience in software engineering, data platforms, or cloud architecture5+ years as a Solution or Enterprise Architect in AWS environmentsProven experience designing and implementing enterprise-scale MLOps platforms or ML lifecycle architecturesStrong experience with cloud-native architectures (microservices, containerization, event-driven systems)Hands-on experience with AWS services and infrastructure designCore Technical ExpertiseMLOps & ML Platform Architecture (Primary Focus)End-to-end ML lifecycle architecture (train ? deploy ? monitor ? retrain)Model governance: lineage, auditability, explainability, responsible AI controlsModel deployment patterns: batch, real-time, and streaming inferenceMonitoring & observability: drift detection, data quality, performance trackingCI/CD for ML and automated deployment pipelinesAWS Cloud ArchitectureDeep expertise in AWS services such as EKS/ECS, Lambda, Step Functions, S3, IAM, VPCExperience designing secure, scalable, multi-account architecturesInfrastructure as Code (CloudFormation or Terraform)Observability, logging, and resilience patternsCloud-Native & Distributed SystemsMicroservices architecture and container orchestration (Docker, Kubernetes)Event-driven architecture (Kinesis, SNS/SQS, EventBridge)Service-to-service communication and resiliency patternsData Architecture (Nice to Have)Experience with enterprise data platforms (data lakes, warehouses, streaming)Familiarity with real-time and batch data processing systemsPreferred QualificationsExperience with enterprise ML platforms (e.g., Domino Data Lab, SageMaker, or similar)Multi-cloud exposure (Azure preferred; GCP is a plus)TOGAF or equivalent architecture frameworkAWS Professional Certification (preferred) or Associate level (required)Security certifications (e.g., CISSP) are a plusWhat This Role Is NOTNot a data scientist or ML model development roleNot a DevOps engineer or pipeline implementation roleNot focused on AIOps or IT operations automationKey Skills & TraitsStrong architectural leadership and decision-making capabilityAbility to define enterprise standards and influence multiple teamsExcellent communication and stakeholder management skillsAbility to translate complex concepts into clear architectural artifactsStrategic thinking with hands-on technical depthEducation Bachelor's degree in Computer Science, Engineering, or related field required Master's degree preferredThanks & Regards,Sekhar PillalaTeam Lead - Talent AcquisitionKMM Technologies, Inc.CMMI Level 2 | ISO 9001 | ISO 20000 | ISO 27000 CertifiedWOSB, SBA 8(A), MDOT MBE & NMSDC MBEContract Vehicles: 8(a) STARS III & Schedule 70Tel: 240-800-1958 | Fax: (866) 856 3684E-MAIL: sekhar.pillala@Linked In:

Created: 2026-05-13