Placement Roles - Senior Architect, Clinical Imaging Platform/ Senior Architect, Algorithm Development Workbench/ Senior Data Architect, Integrated Data Platform- Hybrid- CA

Rek 1

Role: Senior Architect, Clinical Imaging Platform (Hybrid 2-3 Days Onsite/ Week)

Location: San Francisco Bay Area, CA

Duration: 18 - 24+ Months

Job Summary:

Role Overview

IBM Consulting is seeking a Senior Architect to lead the technical design and delivery of a modernized Clinical Imaging Platform for a major regulated life sciences engagement. This role is responsible for defining the end-to-end architecture of a cloud-native imaging infrastructure spanning DICOM ingestion, storage, retrieval, and platform integration within a GxP/SaMD-regulated AWS environment. The platform spans multiple imaging modalities including radiology, digital pathology, and ophthalmology, and serves as the foundational layer for algorithm development, annotation, and regulatory data workflows. The architect will serve as the primary technical authority for the imaging platform layer, working closely with client engineering and data science teams to ensure the platform meets clinical, regulatory, and operational requirements across a polyglot, service-oriented architecture.

Key Responsibilities

Architecture Design and Ownership

• Define and own the technical architecture for a cloud-native clinical imaging platform, covering DICOM/DICOMweb ingestion pipelines, storage hierarchy, and retrieval services across radiology, digital pathology, and ophthalmology modalities
• Lead the redesign of platform data models, including database-level changes to support prospective and retrospective DICOM study ingestion
• Design and govern platform APIs used by downstream consumers including annotation tools, algorithm workbenches, and reporting services
• Establish standards for DICOM metadata management, series/study organization, and cross-modal patient record linkage
• Define and govern the distributed system topology of the platform, including microservices decomposition, event-driven communication patterns, pub/sub messaging, and service mesh design

Durable Workflows and Integration

• Design and implement durable workflow patterns for long-running platform processes including study ingestion, FAIRification pipelines, and cohort preparation, applying durable execution principles to ensure fault-tolerance and recoverability
• Architect integration patterns connecting the imaging platform with external clinical systems, data sources, and downstream consumers, including event-driven and API-based integration topologies
• Define standards for workflow state management, retry and compensation logic, and observability across distributed platform processes
• Evaluate and apply appropriate workflow orchestration and choreography patterns based on process characteristics, without coupling the architecture to a single execution framework

FAIRification

• Architect proactive FAIRification capabilities embedded within the platform ingestion pipeline, ensuring incoming imaging and clinical data is enriched with standardized metadata, controlled vocabularies, and linkage identifiers at ingestion time
• Define FAIR data principles governance across the platform, including data discoverability, accessibility controls, interoperability standards, and reusability metadata
• Design failure handling and validation workflows for FAIRification processes, ensuring data quality and completeness are maintained at scale

Regulated Delivery

• Ensure architecture decisions comply with GxP, SaMD, 21 CFR Part 11, IEC 62304, and applicable ISO standards throughout the design and delivery lifecycle
• Support IQ/OQ/PQ validation activities and produce architecture artifacts required for Computer Software Assurance (CSA) compliance
• Apply ALCOA+ principles to audit trail design and data traceability across the imaging platform

Stakeholder Engagement

• Act as the primary technical counterpart to client domain and imaging architects, facilitating design reviews, architecture decisions, and technical risk escalations
• Collaborate with data, workbench, and regulatory workstreams to ensure platform cohesion across program scope
• Contribute to milestone-based delivery planning, effort estimation, and technical dependency management

Platform Engineering Oversight

• Guide engineering teams on implementation of DICOMweb/WADO-RS endpoints, platform ingestion scheduling, and workflow orchestration
• Define non-functional requirements covering scalability, availability, latency, and disaster recovery for the imaging platform
• Establish observability and monitoring standards using cloud-native tooling within a Roche-managed AWS environment

Required Qualifications

• 10+ years of experience in software or solutions architecture, with at least 5 years focused on medical imaging or healthcare data platforms
• Deep expertise in DICOM standards, DICOMweb protocols, and clinical imaging workflows across multiple modalities including radiology, digital pathology, and ophthalmology
• Hands-on experience designing and deploying cloud-native architectures on AWS (S3, RDS, ECS/EKS, API Gateway, IAM)
• Demonstrated experience designing distributed system topologies including microservices architectures, event-driven systems, pub/sub patterns, and service mesh approaches
• Proficiency in building durable workflow solutions for long-running, fault-tolerant processes, with or without a dedicated durable execution engine
• Proven ability to architect integration solutions connecting platform services with external systems using both event-driven and API-based patterns
• Proficiency in multiple programming languages used across polyglot platform architectures, specifically Java, TypeScript, and Python
• Working knowledge of FAIR data principles and experience applying them within a life sciences or clinical data platform context
• Demonstrated experience delivering within regulated environments governed by GxP, 21 CFR Part 11, or equivalent frameworks
• Strong background in relational database design and distributed data architecture patterns
• Experience leading architecture reviews, producing Architecture Decision Records (ADRs), and working within formal delivery governance structures
• Excellent communication skills with the ability to represent technical positions to both engineering teams and senior business stakeholders

Nice to Have

• Familiarity with SaMD regulatory frameworks including IEC 62304, ISO 14971, ISO 13485, IMDRF, or EU MDR
• Background in digital pathology imaging pipelines, whole slide image (WSI) handling, or ophthalmology imaging workflows
• Prior experience in a fixed-fee, milestone-based engagement model within a large enterprise client environment

Rek 2

Role: Senior Architect, Algorithm Development Workbench (Hybrid 2-3 Days Onsite/ Week)

Location: San Francisco Bay Area, CA

Duration: 18 - 24+ Months

Job Summary:

IBM Consulting is seeking a Senior Architect to lead the design and delivery of an Algorithm Development Workbench for a regulated medical imaging program at a global pharmaceutical and diagnostics company. This role owns the architecture of a managed computational environment supporting the full algorithm development lifecycle: data access, experimentation, model training, validation, and promotion to production. The workbench must operate within a GxP-regulated AWS environment and integrate with platform imaging data, annotation services, and regulatory governance workflows. The architect will collaborate closely with data science, imaging platform, and regulatory workstreams to deliver a reproducible, audit-ready experimentation environment.

Key Responsibilities

Workbench Architecture and Design

• Define the end-to-end architecture of an algorithm development workbench, covering environment provisioning, data access patterns, experiment lifecycle management, and compute resource orchestration
• Design secure, scoped data access mechanisms enabling data scientists to access versioned imaging datasets and annotations without violating data governance or PHI boundaries
• Architect experiment tracking and lineage capabilities, ensuring full reproducibility of model training runs from data version through hyperparameters to model artifact
• Define the promotion pathway from exploratory experimentation to regulatory-grade model validation, including audit trail and artifact management requirements

ML Platform Integration

• Integrate workbench tooling with underlying data lake and imaging platform layers, including versioned dataset APIs, annotation outputs, and study-level data packages
• Define compute environment standards for model training workloads, including GPU resource management, containerization, and dependency isolation
• Establish standards for model packaging, versioning, and handoff to downstream deployment or regulatory validation pipelines
• Collaborate with data architects to define the data access API surface exposed to workbench consumers

Regulated Delivery

• Ensure workbench architecture meets GxP and SaMD requirements for software used in algorithm development for clinical or regulatory purposes
• Design audit trail and logging capabilities covering data access, experiment execution, model versioning, and promotion decisions
• Support IQ/OQ/PQ validation activities and produce required architecture documentation for Computer Software Assurance (CSA) qualification

Stakeholder Collaboration

• Serve as the primary technical lead for the workbench workstream, engaging with client data science, architecture, and regulatory stakeholders
• Partner with the imaging platform and data architecture workstreams to resolve cross-cutting dependencies
• Contribute to program-level architecture reviews, technical risk identification, and milestone delivery planning

Required Qualifications

• 10+ years of experience in software or platform architecture, with at least 4 years focused on ML platforms, MLOps, or algorithm development infrastructure
• Strong background in designing MLOps platforms: experiment tracking, model registries, reproducibility pipelines, and deployment workflows
• Hands-on experience with cloud-native ML platform services, including AWS SageMaker, Google Vertex AI, or equivalent managed ML infrastructure
• Experience with statistical computing and data science environments such as Posit (formerly RStudio) Workbench or equivalent platforms used in regulated research settings
• Familiarity with high-performance computing (HPC) environments and GPU cluster architectures for large-scale model training workloads
• Hands-on experience with cloud-native compute environments on AWS, including container orchestration, IAM, storage integration, and GPU resource management
• Experience integrating ML workbenches with upstream data lakes or feature stores, including versioned data access patterns
• Demonstrated ability to deliver within regulated environments, with familiarity in GxP, 21 CFR Part 11, or IEC 62304 requirements
• Strong communication and stakeholder management skills, with experience translating data science and ML requirements into platform architecture decisions

Nice to Have

• Hands-on experience with NVIDIA AI Workbench, NVIDIA MONAI, NVIDIA Clara, or equivalent medical imaging ML frameworks
• Background in medical imaging algorithm development workflows, including segmentation, classification, or detection model pipelines
• Familiarity with FAIR data principles and reproducible research standards in a life sciences context
• Experience with experiment tracking tools such as Weights and Biases (W&B) or MLflow
• Prior experience in a fixed-fee, milestone-based delivery engagement within a large regulated enterprise environment

Rek 3

Role: Senior Data Architect, Integrated Data Platform (Hybrid 2-3 Days Onsite/ Week)

Location: San Francisco Bay Area, CA

Duration: 18 - 24+ Months

Job Summary:

Role Overview

IBM Consulting is seeking a Senior Data Architect to lead the data modeling and platform design for a next-generation Integrated Data Platform (IDP) supporting a regulated medical imaging program at a global pharmaceutical and diagnostics company. This role is responsible for defining the data architecture across relational and lakehouse layers, governing the structure of versioned study-level data packages, and enabling cross-modal data access for imaging, omics, and real-world data. The architect will design for GxP compliance, FAIR data principles, and scalable query performance within a Roche-managed AWS environment, working in close partnership with the imaging platform, workbench, and clinical data workstreams.

Key Responsibilities

Data Modeling and Architecture

• Lead the design of the Integrated Data Package (IDP) data model, covering multi-modal study assets including DICOM imaging, omics, and real-world data sources
• Define the two-layer data architecture: operational relational layer for study metadata, cataloging, and access registry; lakehouse layer for versioned study assets at scale
• Design schemas, partitioning strategies, and table formats across relational (PostgreSQL) and open table format (Apache Iceberg) layers to support both transactional and analytical access patterns
• Establish cross-modal patient and study linkage standards, including integration with the Global Unique Patient Record Identifier (GUPRI) and related master data entities
• Define data versioning and snapshot strategies for study-level packages, enabling reproducible dataset construction for algorithm development and regulatory submissions

Lakehouse and Query Layer

• Architect the Apache Iceberg-based lakehouse layer on S3, including table design, schema evolution governance, compaction policies, and metadata management
• Design the version catalog architecture using Project Nessie or equivalent catalog tooling, covering namespace structure, branching strategy, and atomic snapshot tagging
• Define query access patterns and optimization strategies across the lakehouse layer using distributed SQL query engines
• Govern the data access API surface exposed to downstream consumers including the algorithm development workbench and reporting services

FAIRification and Data Governance

• Design proactive FAIRification pipelines that enrich incoming study data with standardized metadata, controlled vocabularies, and linkage keys at ingestion time
• Define data quality validation rules, error handling workflows, and observability hooks across the ingestion and enrichment pipeline
• Establish data lineage and provenance tracking across the full data lifecycle from ingestion through version snapshot to analytical consumption
• Ensure data architecture supports GxP audit trail requirements including ALCOA+ principles for traceability, integrity, and contemporaneity

Stakeholder Collaboration and Governance

• Serve as the primary data architecture authority for the program, partnering with imaging platform, workbench, and regulatory workstreams on cross-cutting data decisions
• Engage directly with client data, engineering, and architecture stakeholders to align on data models, access patterns, and governance standards
• Produce and maintain architecture artifacts including data models, schema documentation, ADRs, and data dictionary
• Contribute to milestone delivery planning, technical risk management, and program-level architecture reviews

Required Qualifications

• 10+ years of experience in data architecture, data engineering, or enterprise data platform design
• Expert-level proficiency in relational data modeling (PostgreSQL or equivalent), including schema design, normalization, JSONB/semi-structured patterns, and query optimization
• Hands-on experience designing and operating modern lakehouse architectures using Apache Iceberg or equivalent open table formats (Delta Lake, Apache Hudi)
• Strong background in distributed query engines (Presto, Trino, Spark SQL, or equivalent) and large-scale data partitioning strategies
• Experience with data versioning concepts including snapshot isolation, time travel, schema evolution, and catalog management
• Demonstrated experience delivering data platforms in regulated environments with GxP, 21 CFR Part 11, or equivalent compliance requirements
• Strong written and verbal communication skills, with the ability to document data models and architecture decisions for mixed technical and regulatory audiences

Nice to Have

• Hands-on experience with Project Nessie or equivalent transactional catalog tooling for Iceberg
• Background in medical imaging data (DICOM) or multi-modal clinical data integration including omics or real-world data
• Familiarity with FAIR data principles and their application to life sciences data platforms
• Experience with workflow orchestration tools (Apache Airflow, Temporal, or equivalent) in the context of data pipeline design
• Prior experience in a fixed-fee, milestone-based delivery engagement within a large regulated enterprise environment

Best Regards

Kyle,

Sr. US IT Recruiter

Infinity Tech Group Inc,

12 N Route 17 Suite # 201 Paramus NJ 07652

(Office) Ext 327

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