Own significant product capabilities end-to-end, from ambiguous problem framing through design, implementation, deployment, and iteration with minimal oversight
Locations (4)
Vancouver, British Columbia, Canada
Toronto, Ontario, Canada
Canada
United States
Responsibilities
Own significant product capabilities end-to-end, from ambiguous problem framing through design, implementation, deployment, and iteration with minimal oversight
Build accessible, data-rich user experiences with React and TypeScript that make complex commercial and healthcare insights clear and actionable
Build and maintain real-time computation services (AWS Lambda) that serve scores and calculations on-demand to the customer-facing app, with an eye toward latency, reliability, and cost at scale
Design and maintain reliable, scalable APIs and backend services connecting ODAIA’s data, ML, analytics, and agentic capabilities to customer-facing products
Work across our stack: AWS, Kubernetes, Snowflake, PostgreSQL, and embedded analytical engines like DuckDB and DataFusion
Design, develop, and operate resilient distributed systems and cloud infrastructure for Salesforce’s public cloud platform.
Compensation
The typical base salary range for this position is $148,500 - $223,900 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $178,900 - $246,000 annually.
Responsibilities
Deliver cloud infrastructure automation tools, frameworks, workflows, and validation platforms on our public cloud platforms
Designing, developing, debugging, and operating resilient distributed systems that run across thousands of compute nodes in multiple data centers
Using and contributing to open source technology
Developing Infrastructure-as-Code
Writing microservices on containerization frameworks such as Kubernetes, Docker, Mesos
This role represents a rare opportunity to define and build the AI capabilities of a newly standalone company (DePuy Synthes). You will shape how generative and agentic AI is designed, governed, reused and scaled, while leading a team that turns emerging technologies and priority business needs into enterprise platforms, accelerators and strategic applications.
Locations (2)
Raritan, New Jersey, United States
Bengaluru, Karnataka, India
Compensation
The anticipated base pay range for this position is $140,000.00 - $241,500.00
Responsibilities
Define and evolve the enterprise AI strategy, architecture and roadmap across Databricks Mosaic AI, Amazon Bedrock, AgentCore, the enterprise model gateway and related services.
Architect the agentic runtime, including agent orchestration and mesh, MCP tool and skill registries, Agent-to-Agent interoperability, agent identity, entitlements and secure tool execution.
Design reusable context and knowledge services, including RAG and Graph RAG, vector stores, knowledge graphs such as Amazon Neptune, shared memory and context assembly.
AI Systems Design Architect - Assistant Vice President
Lead end-to-end AI system design and architecture for a major Generative AI platform, ensuring secure, resilient, compliant, and enterprise-aligned solutions.
Compensation
Salary Range: $90,000 - $157,500 Annual
Responsibilities
Own end-to-end architecture and system design for a major AI platform domain, including model integration, orchestration, APIs, data flows, and downstream system interactions.
Define and implement reference architectures, design standards, integration contracts, and non-functional requirements (NFRs) for the platform area.
Translate business and product requirements into scalable, secure, resilient, and maintainable AI solution designs.
Partner with business stakeholders, product managers, engineers, data scientists, platform teams, and security teams to deliver enterprise-ready AI systems.
Design solutions leveraging cloud architecture principles on AWS, Azure, or Google Cloud, ensuring interoperability, scalability, observability, and operational readiness.
Requirements
Bachelor’s degree in Computer Science, Computer Information Systems, Engineering, Mathematics, or a related discipline; Master’s degree preferred.
We are seeking an AI System Design Architect (AVP) with strong expertise in Generative AI, Machine Learning, enterprise architecture, cloud platforms, and scalable solution design.
Compensation
$90,000 - $157,500 Annual
Responsibilities
Own end-to-end architecture and system design for a major AI platform domain, including model integration, orchestration, APIs, data flows, and downstream system interactions.
Define and implement reference architectures, design standards, integration contracts, and non-functional requirements (NFRs) for the platform area.
Translate business and product requirements into scalable, secure, resilient, and maintainable AI solution designs.
Partner with business stakeholders, product managers, engineers, data scientists, platform teams, and security teams to deliver enterprise-ready AI systems.
Design solutions leveraging cloud architecture principles on AWS, Azure, or Google Cloud, ensuring interoperability, scalability, observability, and operational readiness.
Requirements
Bachelor’s degree in Computer Science, Computer Information Systems, Engineering, Mathematics, or a related discipline; Master’s degree preferred.
Lead cloud architecture and engineering workstreams for PwC Southeast Asia Consulting, driving cloud strategy, migration, and implementation across public, private, and hybrid environments.
Responsibilities
Represent PwC in delivery holding a workstream lead for cloud architecture & engineering
Work with customers to understand current state and design future cloud environment
Deliver implementation owning architecture design and planning
Craft cloud strategy and conduct migration assessment
Serve as technical cloud SME to clients
Requirements
Bachelor’s degree in Information Systems, Computer Science, Engineering, or a related field or foreign equivalent
Nice to have: Microsoft Certified Azure Solution Architect Expert
Lead Consultant responsible for end-to-end Atlassian Cloud Transformation projects, including architecture design, migration, security, and team leadership.
Responsibilities
Design and implement Atlassian Cloud architectures
Lead and mentor consulting teams
Coordinate with project managers on planning and risk
Own the AI systems at the heart of the product, building end‑to‑end ML pipelines and cloud architecture for predictive maintenance of commercial fleets.
Compensation
Early-stage compensation: 130 ~ 150k salary, ~1.5% experience and location - we're happy to talk through the details early in the process.
Responsibilities
Build data pipelines that move sensor data from vessel edge devices to cloud over satellite links
Stand up cloud architecture on AWS for real‑time and batch processing
Integrate historical maintenance records from CMMS databases
Develop ML models for anomaly detection and failure prediction using isolation forests, autoencoders, gradient‑boosted trees, and LSTMs
Design fleet‑wide and vessel‑specific modeling approaches
Build the control plane and data plane for physical AI, designing and operating large-scale distributed systems across cloud, on-prem, robotics labs, and edge devices.
Responsibilities
Build a unified execution platform for simulation, policy evaluation, model training, data processing, and deployment
Design workload scheduling and orchestration across CPUs, GPUs, Kubernetes clusters, bare metal, on-prem environments, and edge devices
Build reliable systems for checkpointing, retrying, resuming, scaling, and observing long-running robotics workloads
Create the data infrastructure for video, audio, sensor streams, telemetry, trajectories, policy traces, incidents, and human interventions
Design storage, indexing, lineage, replay, retention, and movement of large multimodal datasets
Establish patterns for LLMOps and MLOps, observability, evaluation, Responsible AI, security and AI cost management in partnership with platform and governance teams.
Create a discoverable catalog of AI services, models, agents, tools, skills and reference patterns that teams can reuse across the enterprise.
Requirements
Bachelor's degree in Computer Science, Engineering or a related technical field
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