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
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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.
Skills Required
- Experience building and operating production ML or GenAI systems in enterprise environments
- Hands-on expertise with LLM orchestration frameworks such as LangChain or LlamaIndex
- Experience with model registries and experiment tracking (e.g., MLflow)
- 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
- Ability to mentor engineers and influence best practices for building scalable, trustworthy AI systems
- 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
BNY Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about BNY and has not been reviewed or approved by BNY.
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Healthcare Strength — Health coverage includes comprehensive options with a $0‑premium plan for eligible lower earners, expanded mental‑health support with personalized therapy, and strong income protection through short‑ and long‑term disability. These features have been recently enhanced and are paired with dental and vision coverage.
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Parental & Family Support — Parental leave provides 16 weeks of fully paid time for all parents, with added support such as adoption assistance. This breadth offers strong coverage for major family events.
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Retirement Support — The 401(k) program includes a company match and Roth options to support long‑term savings. Additional financial programs like tuition assistance and savings vehicles complement retirement readiness.
BNY Insights
What We Do
We help make money work for the world — managing it, moving it and keeping it safe. As a leading global financial services company at the center of the world’s financial system, we touch nearly 20% of the world’s investable assets. Today we help over 90% of Fortune 100 companies and nearly all the top 100 banks globally access the money they need. For 240 years we have partnered alongside our clients to create solutions that benefit businesses, communities and people everywhere.
