Time since we first saw it
Day 39
Similar jobs usually come down between day 4 and day 77.
At BNY Mellon, jobs usually come down by about day 27.
From 51 similar postings that came down, and 101 of BNY Mellon’s. Coming down is not always a hire.
Senior Vice President, AI / Machine Learning Software Engineer
Jersey City, NJ, United States
Live, first seen by us 39 days ago- Pay
$120,000–200,000/year · BaseLocation-specific pay — pay source
BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans. BNY assesses market data to ensure a competitive compensation package for our employees. The base salary for this position is expected to be between $120,000 and $200,000 per year at the commencement of employment. However, base salary if hired will be determined on an individualized basis, including as to experience and market location, and is only part of the BNY total compensation package, which, depending on the position, may also include commission earnings, discretionary bonuses, short and long-term incentive packages, and Company-sponsored benefit programs. This position is at-will and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation) at any time, including for reasons related to individual performance, change in geographic location, Company or individual department/team performance, and market factors.
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingWe are seeking a senior‑level engineer to design, build, and operate production‑grade GenAI and Retrieval‑Augmented Generation (RAG) platforms at scale.
Implement offline and online evaluation frameworks for prompts, models, and datasets, including quality, safety, latency, and cost metrics.
Own end‑to‑end lifecycle management for GenAI systems, covering prompt versions, model versions, datasets, and configurations.
Implement cost and performance monitoring, including token usage, inference latency, throughput, and spend optimization.
From the employer’s posting
We are seeking a senior‑level engineer to design, build, and operate production‑grade GenAI and Retrieval‑Augmented Generation (RAG) platforms at scale. This role focuses on industrializing LLM‑based systems with strong guardrails, observability, evaluation frameworks, and operational rigor, ensuring reliability, safety, and cost efficiency across the full AI lifecycle. This role is located in Jersey City, NJ.
Design and build production‑ready 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 end‑to‑end lifecycle management for GenAI systems, covering prompt versions, model versions, datasets, and configurations.
Implement offline and online evaluation frameworks for prompts, models, and datasets, including quality, safety, latency, and cost metrics. Own end‑to‑end 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.
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, red‑teaming feedback loops, and abuse detection.
What you’ll bring
All qualificationsCore experience
- Strong experience building and operating production ML or GenAI systems in enterprise environments.
- Experience with model registries and experiment tracking, such as MLflow or equivalent.
- Solid understanding of Kubernetes‑based deployments and cloud‑native 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 data‑driven systems.
Preferred experience
- Experience operating LLM systems at scale, including multi‑model or multi‑provider strategies.
- Ability to translate ambiguous GenAI use cases into robust, production‑grade architectures.
Qualification wording
Strong experience building and operating production ML or GenAI systems in enterprise environments.
Experience with model registries and experiment tracking, such as MLflow or equivalent.
Solid understanding of Kubernetes‑based deployments and cloud‑native 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 data‑driven systems.
Experience operating LLM systems at scale, including multi‑model or multi‑provider strategies.
Ability to translate ambiguous GenAI use cases into robust, production‑grade architectures.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 5, 202639 days ago
- Recorded sightings
- 189
- Last seen by us
- Nov 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
BNY Mellon is hiring
57 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring has slowed
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Kubernetes
- MLflow
Where the posting names them
- Experience with model registries and experiment tracking, such as MLflow or equivalent. - Solid understanding of Kubernetes‑based deployments and cloud‑native architectures. - Familiarity with feature stores, data pipelines, and retriever/index lifecycle management.
- Deep hands‑on 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 Kubernetes‑based deployments and cloud‑native architectures.
Your next step
Complete your application on eofe.fa.us2.oraclecloud.com. The employer’s form will show what is required.
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Has BNY Mellon posted this job before?
Yes. We’ve followed 3 other Senior Vice President, AI / Machine Learning Software Engineer jobs there since June 2026. All 3 are still up.
Large employers often post one title for several teams, so these can be separate openings.
Demand for AI Engineer roles
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Job description
At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.
Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance – and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary.
Role Overview
We are seeking a senior‑level engineer to design, build, and operate production‑grade GenAI and Retrieval‑Augmented Generation (RAG) platforms at scale. This role focuses on industrializing LLM‑based systems with strong guardrails, observability, evaluation frameworks, and operational rigor, ensuring reliability, safety, and cost efficiency across the full AI lifecycle. This role is located in Jersey City, NJ.
Key Responsibilities
- Design and build production‑ready 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 end‑to‑end 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, red‑teaming feedback loops, and abuse detection.
- Define and operationalize incident management workflows, including alerting, triage, rollback mechanisms, and post‑incident 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.
Required Qualifications
- Strong experience building and operating production ML or GenAI systems in enterprise environments.
- Deep hands‑on 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 Kubernetes‑based deployments and cloud‑native 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 data‑driven systems.
Preferred Qualifications
- Experience operating LLM systems at scale, including multi‑model or multi‑provider strategies.
- Exposure to AI safety, governance, and compliance frameworks in regulated environments.
- Background in SRE, platform engineering, or MLOps, with a reliability‑first mindset.
- Ability to translate ambiguous GenAI use cases into robust, production‑grade architectures.
What Success Looks Like
- GenAI systems that are observable, measurable, and resilient, not “black boxes.”
- Safe and cost‑efficient RAG pipelines running reliably in production.
- Fast iteration cycles with strong controls, enabling teams to ship GenAI features with confidence.
At BNY, our culture speaks for itself, check out the latest BNY news at:
BNY Newsroom
BNY LinkedIn
Here’s a few of our recent awards:
America’s Most Innovative Companies, Fortune, 2025
World’s Most Admired Companies, Fortune 2025
“Most Just Companies”, Just Capital and CNBC, 2025
Our Benefits and Rewards:
BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life’s journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter.
BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.
BNY assesses market data to ensure a competitive compensation package for our employees. The base salary for this position is expected to be between $120,000 and $200,000 per year at the commencement of employment. However, base salary if hired will be determined on an individualized basis, including as to experience and market location, and is only part of the BNY total compensation package, which, depending on the position, may also include commission earnings, discretionary bonuses, short and long-term incentive packages, and Company-sponsored benefit programs.
This position is at-will and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation) at any time, including for reasons related to individual performance, change in geographic location, Company or individual department/team performance, and market factors.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans. BNY assesses market data to ensure a competitive compensation package for our employees. The base salary for this position is expected to be between $120,000 and $200,000 per year at the commencement of employment. However, base salary if hired will be determined on an individualized basis, including as to experience and market location, and is only part of the BNY total compensation package, which, depending on the position, may also include commission earnings, discretionary bonuses, short and long-term incentive packages, and Company-sponsored benefit programs. This position is at-will and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation) at any time, including for reasons related to individual performance, change in geographic location, Company or individual department/team performance, and market factors.
- Location & working pattern
Jersey City, NJ, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.