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Design and build core AI services for Marketing and Service AI. Implement scalable, low-latency backend APIs powering AI features. Own complex backend services end-to-end with reliability in mind. Evolve agentic architecture: plan tools, calls, and feedback loops. Collaborate with PMs, ML engineers, data scientists; align requirements. Based in Palo Alto hub with regular in-office collaboration. Generous benefits including health, welfare, and wellbeing programs. Equity and competitive total compensation overview. Inclusive culture with growth and learning opportunities.
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Lead cloud engineering team in developing microservices for a multi-tenant platform.
Ensure performance, security, and reliability in cloud service development.
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Define and enhance AI architecture for Service and Marketing capabilities
Lead development of backend systems and APIs for AI products
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Lead integration projects effectively
Map customer needs to API capabilities
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Lead technical vision for client projects
Design, develop, and deploy backend services and APIs
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Build and maintain scalable data pipelines
Improve data models and schema design
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Break down large projects into manageable tasks and deliver them in phases
Collaborate with product, design, and analytics teams on ideation and decisions
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Develop containerized microservices for a distributed system
Process data, real-time events, and network telemetry across clouds
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Lead technical vision for client projects
Develop core backend services with Ruby, Go, and Python
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Develop containerized microservices for a distributed multi-tenant system
Mentor junior engineers, new grads, and interns
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Serve as primary security representative in customer engagements
Articulate security architecture and threat models
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Lead advanced penetration testing activities
Perform security assessments on Cloud Infrastructure
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Lead design and development of core Java backend services.
Optimize platform for high-throughput and low-latency workflows.
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Define roadmap and strategy for ML Data Service platform
Architect scalable data systems
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Design end-to-end data/analytics architecture
Architect scalable data platforms
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Oversee planning and execution across multiple components
Mentor and grow engineers for career development
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Define and drive ML Data Service roadmap and strategy
Architect scalable data ingestion and transformation processes
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Own fleet reliability and define SLOs
Architect infra on GCP and AWS using Terraform for AI workloads
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Promote and enforce information security practices
Identify and report security risks
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Lead design and development of Java backend services
Optimize platform components for high-throughput workflows
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Design and implement features with cross-functional teams
Build scalable frontend/backend code using specified technologies
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Take ownership of quarterly goals and lead the engineering team
Collaborate with product, design, and analytics teams on ideation and decisions
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Advance capabilities in various industries
Gain hands-on experience with key technologies
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Build end-to-end social-channel experiences
Capture profiles, consent, and engagement data
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Implementing and deploying LLM models for conversational agents
Collaborating with cross-functional teams for deployment and scalability
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Lead team in building automated database operations
Orchestrate node lifecycles and cluster operations for DB systems
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Showcasing Databricks' solutions to address business problems
Providing technical leadership for customer evaluation and adoption
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Lead end-to-end migration of media workloads to AWS
Collaborate with stakeholders to set cloud requirements
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Lead and manage a team of engineers effectively
Collaborate with cross-functional teams for ideation and constraints
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Serve as the primary security representative in customer engagements.
Articulate security architecture, controls, and risk management across different layers.
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Promote and enforce information security practices
Understand and evaluate data storage and processing
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Lead and conduct advanced penetration testing
Provide expert guidance on security
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Articulate business and technical value of Neo4j to customers
Lead technology evaluation stages in sales cycles
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Architect and scale AI quality infrastructure
Design end-to-end AI evaluation framework with metrics
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Develop reliable and optimized code
Collaborate to reduce technical debt and resolve customer issues
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Lead design and implementation of scalable systems on AWS and Kubernetes
Support Java-based fintech apps powering core advisor tools
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Implement and maintain standardized patching across various operating systems
Deploy patches using Tanium and troubleshoot deployment issues
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Take ownership of DB and data warehousing infra
Optimize query performance
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Lead and grow a team of engineers
Define and evolve platform architecture for scale
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Build reproducible backtests for models and algorithms
Contribute to differentiated investment services
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Lead and conduct advanced penetration testing
Perform security assessments on cloud environments
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Develop state-of-the-art voice cloning solutions.
Ensure low latency and cost-effective text to speech capabilities.
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Define and execute a product security strategy with AI capabilities
Recruit, develop, and retain top security talent
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Lead and mentor team of Partner Solutions Architects
Serve as senior tech partner to international GTM teams
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Build and maintain large-scale distributed inference systems.
Develop routing and fleet orchestration across accelerators.
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Evaluate cloud infrastructure strategy
Design and implement infrastructure-as-code
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Serve as primary security representative in customer engagements
Drive technical security discussions
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Promote information security practices
Ensure compliance with data privacy standards
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Lead design and development of Java-based backend services
Optimize platform components for high throughput and low latency
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Lead and conduct advanced penetration testing
Define offensive security roadmap
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Drive financial fluency and scalability within Customer Experience operations
Enhance high-touch customer experiences through AI and data utilization