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# Senior Vice President, AI / Machine Learning Software Engineer

- **Company:** The Bank of New York Mellon Corporation
- **Location:** Jersey City, NJ, United States
- **Experience:** Expert
- **Salary:** $200,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Continuous Integration, Machine Learning, Software Safety, Data Logging, Large Language Models, Web Filtering, Build Management, Low Latency, Performance Monitor, Machine Learning Operations, Data Pipelines, Dynatrace
- **Published:** July 10, 2026
- **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17542347?backUrl=%2Fcareer%2F17542347%2FSenior-Vice-President-Ai-Machine-Learning-Software-Engineer-New-Jersey-Jersey-City

## About the Role

* Strong experience building and operating production ML or GenAI systems in enterprise environments.
 * Deep handson expertise with LLM orchestration frameworks, such as LangChain and/or LlamaIndex.
 * Experience with model registries and experiment tracking, such as MLflow or equivalent.
 * Solid understanding of Kubernetesbased deployments and cloudnative architectures.
 * Familiarity with feature stores, data pipelines, and retriever/index lifecycle management.
 * Proven experience implementing telemetry, logging, metrics, and distributed tracing for ML/AI workloads.
 * Strong knowledge of CI/CD practices for ML, GenAI, and datadriven systems.

Preferred Qualifications

 * Experience operating LLM systems at scale, including multimodel or multiprovider strategies.
 * Exposure to AI safety, governance, and compliance frameworks in regulated environments.
 * Background in SRE, platform engineering, or MLOps, with a reliabilityfirst mindset.
 * Ability to translate ambiguous GenAI use cases into robust, productiongrade architectures.

## Description

* Design and build productionready RAG pipelines, including retrieval, ranking, prompt orchestration, and response generation, with comprehensive guardrails, tracing, and observability.
 * Implement offline and online evaluation frameworks for prompts, models, and datasets, including quality, safety, latency, and cost metrics.
 * Own endtoend lifecycle management for GenAI systems, covering prompt versions, model versions, datasets, and configurations.
 * Establish and maintain CI/CD pipelines for prompts, models, and data, enabling safe, repeatable, and auditable releases.
 * Implement cost and performance monitoring, including token usage, inference latency, throughput, and spend optimization.
 * Build and enforce safety mechanisms, such as content filtering, policy enforcement, redteaming feedback loops, and abuse detection.
 * Define and operationalize incident management workflows, including alerting, triage, rollback mechanisms, and postincident analysis.
 * Partner closely with product, platform, and governance teams to ensure GenAI solutions meet enterprise reliability, security, and compliance standards.
 * Mentor engineers and influence best practices for building scalable, trustworthy AI systems.


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