Design, build, and run core services and reusable components for the open-architecture AI platforms, enabling scalable ingestion, metadata-driven processing, governance, and reliable workflow automation. Deliver production-grade capabilities supporting agentic AI solutions
Responsibilities
Design and build backend services and shared libraries that provide platform capabilities
Streaming & batch ingestion frameworks
Metadata-driven pipelines
API and consumption layer integrations
Implement platform security controls including role-based access control, authentication, and integration with enterprise entitlements
Design, build, and maintain distributed systems and algorithms for OCI’s Next Gen Network Observability platform, enabling automated network control and self-healing networks.
Compensation
US: Hiring Range in USD from: $114,600 to $234,600 per annum. May be eligible for bonus, equity, and compensation deferral.
Responsibilities
Design, implement, and maintain critical components of OCI’s Next Gen Network Observability platform.
Build scalable, topology-aware measurement, analytics, and inference systems for data center and WAN networks.
Develop algorithms for path reconstruction, congestion triangulation, queue-wait estimation, fault localization, root cause analysis, and customer-impact attribution.
Ingest and correlate signals from active probes, routing and topology systems, switches, ASICs, queues, flows, logs, metrics, events, and streaming telemetry.
Produce ranked, confidence-scored diagnoses that localize problems to the responsible path, link, queue, device, or shared network resource.
Requirements
Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent professional experience.
Design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services.
Senior/Staff Data Platform Engineer responsible for owning and evolving the Databricks platform on AWS for ModMed’s regulated healthcare data workloads.
Responsibilities
Own Databricks account- and workspace-level capabilities
Build machine learning systems that transform innovative models into secure, reliable, and scalable capabilities for scientists across Pfizer, focusing on AI-enabled drug discovery.
Locations (2)
Bothell, Washington, United States
Tampa, Florida, United States
Compensation
annual base salary ranges from $106,000.00 to $176,600.00
Responsibilities
Own an end-to-end subsystem, platform capability, or workflow
Make sound architecture and design tradeoff decisions
Deliver production-quality software and AI solutions
Drive technical execution for complex projects
Influence engineering standards and best practices
Lead and manage complex technical programs, drive platform transformations, and build TPM discipline within Capital One.
Locations (3)
McLean, Virginia, United States
New York, New York, United States
Richmond, Virginia, United States
Compensation
McLean, VA: $230,400 - $263,000 for Director, Technical Program Management
New York, NY: $251,400 - $286,900 for Director, Technical Program Management
Richmond, VA: $209,500 - $239,100 for Director, Technical Program Management
Responsibilities
Lead programs that deliver critical business goals and build large scale products & platforms
Contribute to TPM / Delivery strategy by establishing operating mechanisms, maturity models, and tooling
Drive development of program roadmap anchored in business objectives
Lead cross-platform technical investment planning and ensure architectural alignment
Senior Director, Quality AI, Data & Technology Engineering
Lead the transformation of Vertex’s global Quality operations through AI, data, and technology, driving strategic vision, roadmap, and execution across multiple business units.
Compensation
$256,000 - $384,000
Responsibilities
Develop and communicate a clear vision for AI-powered Quality technology solutions across Vertex’s global operations
Shape a strategic roadmap applying generative AI, agentic AI, machine learning, data products, and data-driven automation to transform Quality processes
Partner with Quality leadership to accelerate portfolio and commercial priorities while enabling operational excellence
Lead strategic thinking across Quality oversight, inspection readiness, batch release, compliance, and related global Quality activities
Influence stakeholders across a broad internal and external ecosystem to identify and prioritize opportunities for innovation
Requirements
Bachelor’s degree in a relevant field (e.g., Business, Computer Science, Engineering)
Nice to have: Experience leading AI, data, or technology transformation in a global pharmaceutical Quality organization
Nice to have: Experience supporting clinical and commercial supply operations
Nice to have: Experience working across CMC, Manufacturing, Supply Chain, Quality, and R&D functions
Nice to have: Experience partnering with external technology suppliers and service providers in highly regulated environments
Provides technical direction, guidance and support for architectural development that encompasses multiple technology disciplines, platforms and applications.
Compensation
Pay Range: $111,605.00 - $131,300.00
Responsibilities
Design and implement scalable Databricks Lakehouse architectures supporting enterprise data processing, analytics, and high-volume workloads.
Develop data solutions using Databricks, Python, PySpark, Databricks SQL, and Delta Lake.
Modernize and migrate complex Oracle SQL and PL/SQL workloads to Databricks and cloud-based data platforms.
Design and implement high-volume ETL/ELT pipelines, data ingestion, transformation, orchestration, and integration solutions.
Optimize Databricks performance, including SQL queries, data layouts, compute utilization, jobs, and distributed data processing.
Senior AI/ML Engineer with 11 years of experience designing and deploying scalable AI/ML systems, Agentic AI, Lang Chain, Lang Graph, Generative AI and RAG-based applications.
Responsibilities
Design and deploy scalable AI/ML systems
Implement AI architecture design and real-time inference
Build NLP and Generative AI pipelines
Develop model serving architectures using FastAPI and Docker
Create low-latency REST APIs and auto-scaling inference endpoints
Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions
Develop and implement machine learning algorithms, models, and computational systems
design and build scalable data pipelines to support model training and production with DevOps & MLOps
Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements
Engage in research and development of new AI and high-performance compute algorithms, models, and simulations
Requirements
Bachelor's degree or equivalent (minimum 12 years) work experience
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