We are seeking an experienced cloud AI engineer who possesses deep expertise in cloud technologies, data engineering, AI/ML frameworks, infrastructure automation, and cloud security, along with a strong understanding of emerging AI technologies and industry best practices. The Cloud AI Engineer will play a critical role in accelerating AI adoption, improving operational efficiency, optimizing cloud investments, and enabling innovative, enterprise-scale AI solutions that drive business value.
Compensation
WAGE RANGE*: $85-$90
Responsibilities
Architecting and implementing retrieval-augmented generation (RAG) solutions using vector databases, embedding models, semantic search, and enterprise knowledge repositories
Applying enterprise AI security practices including identity and access management, data privacy, prompt injection mitigation, content filtering, responsible AI principles, and governance controls
Optimizing AI workloads through intelligent model selection, token usage management, caching, efficient retrieval strategies, latency reduction, and cloud resource optimization
Integrating LLM-powered applications and AI agents with enterprise systems, cloud services, databases, and APIs using secure integration patterns, MCP-based tool connectivity, and event-driven architectures
Designing, building, and deploying AWS-hosted data solutions, including large-scale data processing pipelines, computationally intensive statistical modeling, and advanced analytics
Requirements
Bachelor's degree (or equivalent) in computer science, information technology, or mathematics
Lead the creation and operation of a complex, constraint-based optimization and recommendation ecosystem supporting the bank’s operations, integrating time-series predictions and demand forecasts with optimization models.
Compensation
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.
Responsibilities
Lead the design and delivery of a complex constraint-optimization recommendation system
Formulate global, system-wide optimization objectives and constraints
Develop and validate time-series and demand-driven predictive models
Build and lead a multidisciplinary team of applied AI/ML researchers, optimization specialists, and engineers
Drive significant business stakeholder management across executive leadership and product, business, analytics, data, and engineering partners
Requirements
PhD in Computer Science in Artificial Intelligence, Operations Research, or a closely related quantitative discipline
Nice to have: advanced research or specialized doctoral work at the intersection of AI/ML, time-series forecasting, demand modeling, and constraint optimization
Nice to have: deep experience with distributed infrastructure
Nice to have: deep experience with distributed ML and scalable optimization
Nice to have: deep experience with production model lifecycle management
Lead technical partnership engagements with AI and enterprise technology developers, evangelizing Apple’s AI/ML frameworks and platform technologies to drive adoption and integration.
Locations (3)
Austin, Texas, United States
Cupertino, California, United States
New York City, New York, United States
Responsibilities
Own Partner Technical Relationships
Drive Platform Adoption
Lead Technical Workshops & Architecture Reviews
Act as Trusted Technical Advisor
Partner Across Business Development & Field Teams
Requirements
Bachelor's degree in Computer Science, Engineering, or a related field
Nice to have: 12+ years of experience in a technical role
Provide technical account management for HPC and cloud customers, resolving complex hardware and software issues and ensuring customer satisfaction.
Compensation
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package.
Responsibilities
Work with NVIDIA Cloud and Enterprise customers to resolve sophisticated technical issues
Own and resolve customer issues during installation, operation, maintenance or product application
Work with the latest hardware and software technologies such as ML frameworks and tools like Spark, Kubernetes, and Ceph
Be a technical resource, develop, re-define, and document standard methodologies for support processes
Requirements
Bachelors degree or equivalent experience
Nice to have: large-scale HPC or AI cluster environments
Design, architect, and lead implementation of Workday Financials with AI and automation focus.
Responsibilities
Assess current finance systems, applications, data flows, and processes to design a scalable future-state architecture centered around Workday Financials.
Lead the design and implementation of Workday Finance solutions aligned with organizational strategy and growth objectives.
Establish enterprise-wide Workday roadmap and technology governance strategy.
Define end-to-end system architecture including integrations, data models, security, and reporting frameworks.
Partner with Finance stakeholders to translate business requirements into scalable, efficient technical solutions.
Requirements
Bachelor’s degree in Computer Science, Information Systems, Finance Technology, or related field.
Software Development Engineers are expert problem-solvers and builders who design, implement, and improve software applications and systems.
Compensation
For roles located in the US, the estimated salary range for this position is $133,300.00 to $ 213,400.00 USD per year, which may include potential sales incentive payments (if applicable).
Responsibilities
Collaborate with stakeholders to determine requirements for product components and incorporate feedback into future designs or solutions.
Translate functional requirements into system designs and communicate component interactions, ensuring alignment with business needs and timelines.
Design and develop product components, refine code plans, and lead design reviews to ensure completeness and adherence to requirements.
Contribute to project estimation, considering delivery costs and escalating issues that may cause delays.
Lead by example in creating, implementing, and maintaining extensible, reusable code, and drive code quality through metrics and best practices.
Adapt AI models across platforms to enable performance and accuracy measurement on Linux and Windows hosts, x86 and Arm environments, mobile and target devices, MTPs, instruction-set simulators (ISS), and supported Hexagon architectures.
Design, implement, and maintain system-integration, regression, preflight, and release-validation workflows.
Analyze failures, crashes, output mismatches, accuracy changes, and performance regressions.
Integrate test workflows with Git, GitHub or Gerrit, CI systems, scheduled jobs, service accounts, target stations, and automated result distribution.
Improve test coverage, reproducibility, execution time, environment stability, and visibility into regression health and release readiness.
Requirements
Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, or a related field
Nice to have: Experience testing embedded, DSP, accelerator, or heterogeneous-compute systems
Nice to have: Experience with C or C++
Nice to have: Experience with pytest
Nice to have: Experience performing cross-platform validation
Annual Salary Range for jobs which could be performed in Canada CAD 114,890.00-162,190.00
Responsibilities
Analyzing performance issues in compiler-generated code and identifying root causes within optimization and code generation stages.
Measuring and tuning application performance on Intel CPUs and GPUs while tracking regressions and identifying optimization opportunities.
Designing and implementing automated testing solutions to continuously monitor compiler performance and quality.
Bridging Intel hardware and compiler capabilities with AI and HPC software ecosystems, including PyTorch, inference frameworks, and machine learning workloads.
Contributing to open-source compiler communities through issue reporting, patch development, code reviews, and technical discussions.
Requirements
Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field
Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field
Nice to have: open-source contribution history
Nice to have: strong written and oral communication skills
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