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About This Role
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 .
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.
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Required Qualifications
- Advanced degree in STEM engineering degree, or equivalent work experience with experience preferred in related fields. 7\-9 years of related experience required; experience in the securities or financial services industry is a plus
- 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 .
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 Mellon is an Equal Employment Opportunity/Affirmative Action Employer. Minorities/Females/Individuals with Disabilities/Protected Veterans. Our ambition is to build the best global team\-one that is representative and inclusive of the diverse talent, clients and communities we work with and serve\-and to empower our team to do their best work. We support wellbeing and a balanced life, and offer a range of family\-friendly, inclusive employment policies and employee forums.
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 $190,000 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.
Salary Context
This $120K-$190K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $183K across 194 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At BNY, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $219,250 based on 424 positions with disclosed compensation. This role's midpoint ($155K) sits 29% below the category median. Disclosed range: $120K to $190K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
BNY AI Hiring
BNY has 2 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer. Positions span Jersey City, NJ, US, Pittsburgh, PA, US. Compensation range: $190K - $190K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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