Senior hands‑on technical leader responsible for architecting, engineering, and delivering enterprise‑scale GenAI and Intelligent Automation solutions across cloud and enterprise AI platforms.
Locations (2)
Dallas, Texas, United States
Farmers Branch, Texas, United States
Responsibilities
Architect and deliver scalable, secure, resilient GenAI, RAG, Agentic AI, Document AI, and Virtual Assistant solutions.
Provide hands‑on leadership across architecture, design, prototyping, coding, deployment, troubleshooting, and production support.
Lead Applied AI Engineer/Scientist responsible for designing, developing, evaluating, and continuously improving applied AI systems to solve high-value construction and business problems.
Responsibilities
Define business problem and data readiness
Audit real-world inputs
Design data-labeling and validation approaches
Maintain traceability of outputs
Architect end-to-end AI agents and workflows
Requirements
Bachelor’s or advanced degree in computer science, machine learning, data science, engineering, or a related field
Design, develop, test, deploy, and support intelligent automation solutions across business processes with SAP Business Process Automation (BPA).
Compensation
Pay Rate: 90$/hour on Incorp.
Responsibilities
Design, develop, test, deploy, and support intelligent automation solutions across business processes with SAP Business Process Automation (BPA).
Execute end-to-end implementation of SAP Build Process Automation solutions, including process automation, workflows, and business rules.
Develop automated SAP workflows, business rules, approvals, forms, validations, and unattended automations.
Integrate SAP BPA with SAP S/4HANA using OData services, BAPIs, REST APIs, CAP, and other SAP / non-SAP interfaces, enabling business transformation through automation.
Develop and support SAP Document Information Extraction (DOX) solutions for document extraction and processing.
AI Test Engineering is a hands-on role within VLabs Quality Engineering, responsible for validating the performance, reliability, and integrity of AI-enabled solutions in production environments.
Responsibilities
Translate AI testing strategy into executable test scenarios across LLM outputs, document classification, extraction accuracy, agent workflows, and edge cases
Design adversarial and boundary test inputs to expose hallucination, misclassification, and failure modes
Validate AI outputs for structure, consistency, accuracy, and production readiness against defined performance thresholds
Build reusable Python-based evaluation frameworks, including output validation, hallucination detection, and scoring mechanisms
Develop parameterized test scripts reusable across features, models, and releases
Requirements
Bachelor’s degree
Advanced degree in Computer Science, Data Science, or related field preferred
Nice to have: Background in regulated or compliance-driven environments
Lead data migration and integration for legacy systems to cloud platforms, ensuring data quality, governance, and seamless integration with Salesforce and MuleSoft.
Locations (2)
Reston, Virginia, United States
United States
Compensation
The pay range for this position based on full-time employment is: $98,614.00 - $167,644.00
Responsibilities
Lead end-to-end data migration from legacy systems to cloud platforms, including data mapping, transformation, and validation (Salesforce-centric).
Analyze and convert unstructured, document-heavy data into structured, analytics-ready formats using Document AI.
Implement data quality processes (cleansing, deduplication, reconciliation) to ensure accuracy and completeness post-migration.
Support phased migration and system cutover with minimal operational disruption.
Design, build, and maintain MuleSoft integrations, including API development for real-time and batch data exchange.
Develop and implement AI-powered document-processing solutions to automate the extraction and validation of critical information for corporate actions.
Compensation
$118,000—$152,000 CAD
Responsibilities
Develop and implement AI-powered document-processing solutions to automate the extraction and validation of critical information from lengthy corporate-action announcements, notices and supporting documentation.
Apply corporate actions and asset servicing expertise to understand event requirements, elections, entitlements and exception-processing workflows.
Use Python, APIs, LLMs and document AI technologies to develop extraction, validation and automation capabilities that support efficient and accurate securities processing.
Translate business rules and operational requirements into technical logic, ensuring solutions accurately reflect corporate-action processing requirements and validation needs.
Collaborate with business and technology stakeholders to identify processing challenges, test and refine solutions, and improve operational efficiency, processing capacity and scalability.
Requirements
Nice to have: ISO 15022
Nice to have: ISO 20022
Nice to have: Corporate Actions Developer
Nice to have: Asset Servicing Technology Analyst
Skills
Startup Business Development Lead - Snowflake for Startups
Lead business development for AI-native startups, building relationships, executing GTM strategies, and driving adoption of Snowflake AI products.
Compensation
The estimated base salary range for this role is $140,000 - $201,200. Additionally, this role is eligible to participate in Snowflake’s bonus and equity plan.
Responsibilities
Build and grow relationships with high-priority AI-native startups, founders, venture investors, and ecosystem partners
Develop and execute a startup GTM strategy to accelerate adoption of Snowflake with a heavy emphasis on Snowflake’s AI products
Serve as a trusted voice on AI-native startup trends, including model usage, data infrastructure, agentic workflows, and enterprise adoption patterns
Help founders understand how to build and scale AI applications with Snowflake, including Cortex AI, Cortex Agents, Cortex Search, Document AI, Snowpark ML, and related platform capabilities
Partner with Sales, Solutions Engineering, Product, Marketing, AI Partnerships, and Snowflake Ventures to drive coordinated startup acquisition and expansion motions
Develop custom software solutions to design, code, and enhance components across systems or applications using modern frameworks and agile practices.
Responsibilities
Oversee end-to-end Data 360 delivery by governing data ingestion (batch, streaming, APIs, Zero Copy), data modeling and identity unification, Data Transforms and Calculated Insights, and effective segmentation and activation across Marketing Cloud, Personalization, and AI-driven use cases.
Own solution design reviews and ensure alignment with enterprise data architecture.
Prepare data modeling, DMOs, and relationship design.
Act as the primary technical and delivery point of contact for Data 360 initiatives.
Ensure best practices for scalability, performance, and data governance.
Requirements
Nice to have: Integrating Data Cloud with Marketing Cloud, Sales Cloud, and Service Cloud
Nice to have: Knowledge of Marketing Cloud Journeys, Contact Builder, and activation flows
Nice to have: Exposure to Salesforce Personalization, Agentforce, and Einstein AI
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