
5001 - 10000 employees
đŁ Marketing
đ¸ Finance
đł Fintech
Marketing ⢠Finance ⢠Fintech
Vericast is a company focused on accelerating the performance of financial institutions. Through the use of data, artificial intelligence, and innovative strategies, Vericast helps banks and credit unions drive growth and enhance their marketing performance. The company provides a variety of solutions including digital marketing, direct mail, card solutions, check solutions, customer and employee insights, and customer change management. Vericast leverages responsibly sourced data to engage consumers effectively, which is why many financial institutions trust them for solving marketing challenges. Their expertise in the financial sector is aimed at delivering insights and growth solutions, positioning them as a leader in financial marketing services.
đĽ 0 minutes ago
đ¤ Texas â Remote
đľ $120k - $140k / year
â° Full Time
đ Senior
đ´ Lead
đ¤ AI Engineer
đť Ghost score 0%
Airflow
AWS
Azure
Cloud
ETL
JavaScript
Kubernetes
Microservices
Node.js
OpenShift
PySpark
Spring
Spring Boot
SpringBoot
SQL
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5001 - 10000 employees
đŁ Marketing
đ¸ Finance
đł Fintech
Marketing ⢠Finance ⢠Fintech
Vericast is a company focused on accelerating the performance of financial institutions. Through the use of data, artificial intelligence, and innovative strategies, Vericast helps banks and credit unions drive growth and enhance their marketing performance. The company provides a variety of solutions including digital marketing, direct mail, card solutions, check solutions, customer and employee insights, and customer change management. Vericast leverages responsibly sourced data to engage consumers effectively, which is why many financial institutions trust them for solving marketing challenges. Their expertise in the financial sector is aimed at delivering insights and growth solutions, positioning them as a leader in financial marketing services.
⢠Design, develop, deploy, and support Agentic AI applications, including multi-agent workflows and orchestration ⢠Provide hands-on technical collaboration, code review, support, and mentorship to AI Engineers and contractors ⢠Architect and implement RAG pipelines, vector search, embedding-based retrieval, and LLM integration patterns for production use cases ⢠Design and build MCP Server integrations and tool-use frameworks ⢠Collaborate with the VP Engineering and Data Strategy and cross-functional stakeholders to translate AI strategy and roadmap into technical execution plans ⢠Own selection and integration of AI frameworks and platforms for scalable, reliable, and secure solutions ⢠Establish and enforce engineering best practices, including CI/CD, testing, and responsible AI guardrails ⢠Monitor emerging AI engineering trends, tools, and techniques and assess applicability ⢠Participate in continuous improvement teams, recommend and implement improvement ideas, and participate in training ⢠Support and comply with internal and external audits, including providing information, performing assigned tasks, and maintaining evidence ⢠Support and comply with safety and security policies
⢠Bachelor's Degree in a technical or numerical field (Required) ⢠Master's degree preferred ⢠8+ years' experience designing and developing software applications and/or data engineering pipelines ⢠3+ years' experience leading or providing technical direction to engineers on application or AI/ML delivery teams ⢠Experience in LangGraph, LangChain, RAG chatbots, vector databases, NLP-based automation, MCP Server development, embedding-based search, and LLM integration is required ⢠Experience in microservices architecture, Kubernetes, OpenShift, AWS and/or Azure, Spring Boot, Node.js, CI/CD, and DevOps automation is required ⢠Experience with Trino, Superset, Starburst SQL Server, ETL tools, S3, Airflow, Iceberg, PySpark, or Hive preferred ⢠Experience building financial services solutions in big data infrastructure preferred ⢠Strong hands-on expertise in machine learning frameworks, agentic AI architecture, and cloud computing platforms ⢠Proven ability to lead technical delivery and mentor engineers in a fast-paced environment ⢠Strong communication and facilitation skills; able to translate business requirements into technical designs ⢠Working understanding of AI ethics, data privacy, and regulatory considerations relevant to AI systems ⢠AWS Certified Machine Learning Engineer - Associate (MLA-C01) or AWS Certified AI Practitioner preferred ⢠Microsoft Certified: Azure AI Engineer Associate (AI-102) preferred ⢠Google Cloud Professional Machine Learning Engineer preferred ⢠NVIDIA AI/Deep Learning certification preferred ⢠Databricks Machine Learning Associate preferred
⢠Medical coverage ⢠Dental coverage ⢠Vision coverage ⢠401K matching ⢠Flexible PTO ⢠Life insurance ⢠Employee assistance ⢠Pet insurance ⢠Training and development activities ⢠Disability accommodations during the selection process
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