Lead Software Engineer-AI Platform Engineer

$152K - $215K Jersey City, NJ, US Senior AI Software Engineer

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Skills & Technologies

AwsAzureDockerGcpKubernetesMlflowPythonPytorchRag

About This Role

AI job market dashboard showing open roles by category

JOB DESCRIPTION

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the Corporate Sector, specifically as a part of the Infrastructure Platforms team, you will play a crucial role in an agile team committed to enhancing, creating, and delivering high\-quality technology products in a secure, stable, and scalable manner. Your role as a vital technical contributor will involve developing critical technology solutions across numerous technical domains within various business functions, all aimed at supporting the firm's business goals.

Job Responsibilities:

  • Execute creative software solutions, including design, development, and technical troubleshooting, with the ability to think beyond conventional approaches to build solutions or resolve technical problems.
  • Develop secure, high\-quality production code, and review and debug code written by others.
  • Identify opportunities to eliminate or automate the remediation of recurring issues to enhance the overall operational stability of software applications and systems.
  • Lead evaluation sessions with external vendors, startups, and internal teams to drive outcomes\-oriented assessments of architectural designs, technical credentials, and their applicability within existing systems and information architecture.
  • Lead communities of practice across Software Engineering to promote awareness and adoption of new and leading\-edge technologies.
  • Contribute to a team culture of diversity, equity, inclusion, and respect.
  • Develop and deploy cloud infrastructure platforms that are secure, scalable, and optimized for AI and machine learning workloads.
  • Collaborate with AI teams to understand computational needs and translate these into infrastructure requirements.
  • Monitor, manage, and optimize cloud resources to maximize performance and minimize costs.
  • Design and implement continuous integration and delivery pipelines for machine learning workloads.
  • Develop automation scripts and infrastructure as code to streamline deployment and management tasks.

Required Qualifications, Capabilities, and Skills:

  • Formal training or certification in software engineering concepts with 5\+ years of applied experience.
  • Hands\-on practical experience in delivering system design, application development, testing, and ensuring operational stability.
  • Proficiency in at least one programming language, such as Python, Go, Java, or C\#.
  • Proficiency in automation and continuous delivery methods.
  • Proficient in all aspects of the Software Development Life Cycle.
  • Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).
  • Foundational understanding of machine learning concepts, including transformer architecture, ML training, and inference.
  • Experience in solutions design and engineering, containerization (Docker, Kubernetes), and cloud service providers (AWS, Azure, GCP).
  • Experience with Infrastructure as Code.
  • Deep understanding of cloud component architecture: Microservices, Containers, IaaS, Storage, Security, and routing/switching technologies.

Preferred qualifications, capabilities, and skills* Foundational understanding of NVIDIA GPU infrastructure software (e.g., DCGM, BCM, Triton Inference).

  • Hands\-on experience with machine learning frameworks such as PyTorch and TensorBoard.
  • Proficiency with observability tools like Prometheus and Grafana.
  • Experience in ML Ops and related tooling, including MLflow.
  • Background in high performance computing and ML frameworks (e.g., vLLM, Ray.io, Slurm).
  • Strong knowledge of network architecture, database programming (SQL/NoSQL), and data modeling.
  • Familiarity with cloud data services, big data processing tools, and Linux environments (scripting and administration).

ABOUT US

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission\-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on\-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase \& Co. is an Equal Opportunity Employer, including Disability/Veterans

ABOUT THE TEAM

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.

Salary Context

This $152K-$215K range is below the median for AI Software Engineer roles in our dataset (median: $189K across 518 roles with salary data).

Role Details

Company JPMorganChase
Title Lead Software Engineer-AI Platform Engineer
Location Jersey City, NJ, US
Category AI Software Engineer
Experience Senior
Salary $152K - $215K
Remote No

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 26,159 AI roles we're tracking, AI Software Engineer positions make up 2% of the market. At JPMorganChase, 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

Aws (34% of roles) Azure (10% of roles) Docker (4% of roles) Gcp (9% of roles) Kubernetes (4% of roles) Mlflow (1% of roles) Python (15% of roles) Pytorch (4% of roles) Rag (64% of roles)

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 $235,100 based on 665 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($183K) sits 22% below the category median. Disclosed range: $152K to $215K.

Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.

JPMorganChase AI Hiring

JPMorganChase has 192 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, Data Scientist, AI Agent Developer. Positions span Columbus, OH, US, New York, NY, US, San Francisco, CA, US. Compensation range: $62K - $500K.

Location Context

Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.

The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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

Based on 665 roles with disclosed compensation, the median salary for AI Software Engineer positions is $235,100. Actual compensation varies by seniority, location, and company stage.
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.
About 7% of the 26,159 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
JPMorganChase is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Software Engineer positions include Staff Engineer, AI Architect, Engineering Manager. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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