Lead the design, development, and deployment of GenAI solutions and architect cloud-native applications for Visa’s Legal Technology organization.
Responsibilities
Lead the design, development, and deployment of GenAI solutions, including LLM integration, prompt engineering, RAG systems, and domain‑specific model customization.
Evaluate emerging AI capabilities and prototype innovative solutions to accelerate business transformation.
Drive experimentation frameworks that validate model performance, user experience impact, and production feasibility.
Architect cloud‑native applications capable of handling large‑scale, high‑availability workloads.
Oversee performance optimization, distributed processing, caching strategies, and operational monitoring.
Lead the design and operation of scalable batch and streaming data pipelines and trusted data context layers for Cisco’s Network Platform, ensuring data quality, observability, and AI readiness across structured and unstructured data.
Locations (5)
San Jose, California, United States
New York City, New York, United States
Washington, United States
Illinois, United States
Canada
Compensation
The starting salary range posted for this position is $167,700.00 to $245,200.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.
Design and build scalable batch and real‑time data platforms, own architecture of ingestion, orchestration, monitoring, and governance, and collaborate with clients and cross‑functional teams to deliver enterprise‑grade data solutions.
Responsibilities
Design and build scalable batch and real‑time data platforms
Own the architecture of ingestion patterns, orchestration, lineage, monitoring, security, governance, and resilience
Develop enterprise‑grade ETL and ELT pipelines across cloud and hybrid landscapes
Integrate enterprise systems such as ERPs, CRMs, identity platforms, APIs, streaming systems, and legacy applications
Build data products that support analytics, machine learning, GenAI, RAG, and agentic AI applications
Architect, build, and scale a global data ecosystem for AI-based ground truth generation for autonomous driving and robotics.
Responsibilities
Develop and productionize AI-powered auto-labeling workflows using computer vision models, vision-language models, and AI agents, integrating human review where needed.
Design and implement MLOps capabilities for reproducible training and inference, model and dataset versioning, evaluation, deployment, and lifecycle management.
Build observability and data quality frameworks covering pipeline health, job execution, labeling quality, data lineage, and GT release readiness.
Optimize distributed processing and GPU inference workloads to improve throughput, resource utilization, cost efficiency, and release turnaround time.
Drive technical decisions and cross-functional execution with perception, autolabeling modeling, data operations, and partner-facing teams to translate requirements into production solutions.
Requirements
BS, MS, or PhD in Computer Science, Software Engineering, Data Engineering, or a related field, or equivalent practical experience.
Lead the design, development, and maintenance of forecasting models for recognized revenue and cost of goods sold, integrating data science, finance, and engineering practices.
Compensation
Base Pay Range For US Locations: $148,000—$222,000 USD
Responsibilities
Build and maintain forecasting models for recognized revenue and COGS
Link product usage drivers to revenue and cost metrics
Scale forecasting systems across multiple horizons
Partner with Finance, FP&A, Product, Engineering, and Data Science teams
Monitor model performance and conduct variance investigations
Requirements
Bachelor's or advanced degree in Statistics, Mathematics, Computer Science, Economics, Finance, Engineering, or related quantitative field
Support DCDC with developing and implementing software capabilities for big data processing and cyberspace data analysis.
Compensation
$135,000 - $216,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual’s experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.
Responsibilities
Lead the design, development, integration, deployment, and sustainment of software applications, services, libraries, and analytic pipelines for cyber operational data.
Develop batch and streaming data ingestion, parsing, normalization, enrichment, correlation, indexing, and query functions across distributed data platforms.
Work with cyber operators, threat analysts, data engineers, and Government leads to translate mission questions, telemetry limitations, and analytic requirements into tested software.
Mentor developers, establish coding and review practices, assess technical tradeoffs, and document designs, source code, tests, interfaces, and deployment procedures.
Design and integrate APIs, microservices, data interfaces, and event-driven services using documented contracts and appropriate protocols.
Design, code, test, debug, document and maintain the services that make up the AI platform and agent runtime, taking systems from design review through production operation and long-term support.
Responsibilities
Design, code, test, debug, document and maintain the services that make up the AI platform and agent runtime
Design the public surface of the platform - APIs, SDKs, client libraries, schemas and versioning strategy
Build the Capability Gateway using MCP servers and tool interfaces
Build and operate the agent harness and runtime
Establish engineering standards, methods and tooling (coding standards, CI/CD, infrastructure as code)
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