Summer 2026
Associate Intern
New Markets
Posted on 4/18/2026
Apollo Global
1,001-5,000 employees
Alternative investment manager with distressed expertise
Compensation Overview
$84.13/hr
New York, NY, USA
In Person
MBA, JD
 Product (1) |
|---|
Get referred to Apollo Global
See people who can refer or advise you
- Pursuing an MBA or JD/MBA (Class of 2027) with an excellent academic record and a demonstrated interest in finance through previous internships, jobs, and coursework.
- 2-5 years of experience in investment banking, asset management, private markets, consulting, or a related field.
- Strong financial modeling skills, including valuation techniques, scenario analysis, and structuring expertise.
- Ability to analyze new market opportunities and develop insights to shape product development strategies.
- Exposure to capital raising, Mergers and Acquisitions, structured finance, or investment vehicles, with an understanding of how to structure new investment products.
- Experience working in ambiguous, fast-paced environments where product structures, investor preferences, and regulations are evolving.
- Ability to juggle multiple projects and work cross-functionally to bring new solutions to market efficiently.
- Strong communication and presentation skills, with experience developing pitch decks, investment memos, and marketing materials that effectively communicate complex investment ideas.
- Understanding of private equity, private credit, hedge funds, structured products, and their potential adaptation to new investor markets.
- Product Development & Strategy: Assist in the end-to-end design, structuring, and execution of cutting-edge investment products, including Defined Contribution solutions, tax-advantaged vehicles, and private market ETFs.
- Market Expansion & Validation: Conduct in-depth market research and feasibility studies to assess the viability of new investment solutions and their potential adoption across different investor segments.
- Financial & Competitive Analysis: Build financial models, perform valuation analyses, and assess competitive positioning to inform product design and pricing strategies.
- Go-to-Market Execution: Collaborate with investment, distribution, legal, and compliance teams to develop frameworks for launching and scaling first-to-market products.
- Data-Driven Decision Making: Develop insights from investor behavior, industry trends, and macroeconomic data to refine product strategy and positioning.
- Storytelling & Communication: Translate complex investment strategies into compelling narratives for internal stakeholders, distribution teams, and investors.
- Operational Infrastructure & Scaling: Design and implement processes to efficiently launch, distribute, and manage new investment products at scale.
Apollo Global Management is a global manager of alternative investments. It invests on behalf of clients in private equity, credit, and real estate, with a focus on distressed opportunities and value-oriented strategies. It operates its businesses in an integrated way across asset classes, using capital to back the balance sheets of industry-leading companies. The company has a 26-year history of deploying capital through different economic cycles and aims to create value for its investors. What sets Apollo apart is its combination of cross-asset expertise, distressed investing know-how, and its integrated platform, which it uses to pursue opportunities where others may not. Its goal is to generate returns for investors by applying its contrarian, value-oriented approach across private equity, credit, and real estate investments.
Company Size
1,001-5,000
Company Stage
IPO
Headquarters
New York City, New York
Founded
1990
Get referred to Apollo Global
See people who can refer or advise you
Simplify's Take
What believers are saying
- August 11, 2026 Nvidia named Apollo in a $500 billion AI-infrastructure financing coalition.
- August 2026 European Commission approved Apollo's Atlantic Aviation acquisition, expanding aviation-services cash flow.
- Apollo's 2026 fundraising momentum improves dry powder, especially after strong investor demand for Fund XI.
What critics are saying
- August 2026 Nvidia financing platforms tie Apollo to opaque AI-debt underwriting and circular-demand scrutiny.
- EasyJet's £5.7 billion deal exposes Apollo to airline fuel shocks, labor disputes, and regulatory delays.
- If credit spreads widen in 2026, Apollo's fundraising, exits, and fee growth all compress together.
What makes Apollo Global unique
- Apollo's integrated credit, equity, and real-asset platform still differentiates it on cycles.
- August 2026 easyJet takeover shows Apollo can source proprietary, large-cap European public-to-private deals.
- Apollo raised over $12 billion for Fund XI in 2026, validating LP loyalty.
Help us improve and share your feedback! Did you find this helpful?
Benefits
Performance Bonus
Company News
NVIDIA AI factory compute is becoming an investable asset class. KIBU announced partnerships with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to establish independent financing platforms designed to mobilize over $500 billion of third-party capital to support the buildout of AI infrastructure over time. This is a major milestone for NVIDIA and the AI industry. KIBU has moved from an era in which companies bought chips and built data centers project by project to one in which AI factories can be financed as productive infrastructure - with repeatable platforms, long-term institutional capital and a diverse customer base that uses compute to create revenue. AI has reached an inflection point. It is moving from research into production. AI is creating real value, and the infrastructure behind it is becoming one of the world's most productive assets. In AI, compute is revenue. A new infrastructure asset. NVIDIA compute is not just a chip. It is a complete AI factory platform including accelerated computing, networking, systems software, AI frameworks and a global developer ecosystem. NVIDIA DSX AI factories can run the world's broadest range of AI models, modalities and algorithms - language, vision, speech, biology, physical AI and robotics. One NVIDIA AI factory can serve many customers and many workloads. That makes it flexible and fungible. It is also built on a globally adopted architecture used across every major cloud, and by systems makers and enterprises around the world. When needs change, the factory can be used by another customer, another cloud or another operator. This broad ecosystem gives NVIDIA compute a deep market of potential users and offtakers, helping protect residual value. CUDA makes the factory better over time. Every generation of NVIDIA software improves the performance, efficiency and total cost of ownership of already- installed infrastructure. The hardware does not stand still: software innovation allows an AI factory to produce more intelligence at lower cost throughout its life, extending its useful economic value. NVIDIA A100 is a powerful example. NVIDIA introduced the Ampere-based A100 in 2020, and six years later, it remains in active commercial use for AI training, fine-tuning, inference and high-performance computing. Customers continue to commit capacity for multi-year deployments, extending A100's economic life toward a decade. The market is also demonstrating the durability of NVIDIA compute economics. One-year H100 rental pricing rose from about $1.70 per GPU-hour in October 2025 to about $2.35 per GPU-hour in March 2026. Cross-provider on-demand median pricing rose from roughly $2.00 per GPU-hour in October 2025 to $2.70 in June 2026. Blackwell capacity commands a premium, with reported B200 cloud rates spanning approximately $5.30 to $7.05 per GPU-hour. That is what makes NVIDIA AI factories different. Their value is not fixed at installation: CUDA continuously improves their output; the installed base remains productive well beyond its initial depreciation period; and the same standard architecture serves a deep, growing global market of AI workloads. These are the characteristics of an investable infrastructure asset: it produces revenue, serves a broad market, improves in performance over time and can be redeployed. Bringing capital to AI factories. The demand for AI infrastructure is extraordinary. But access to capital is uneven. Many great AI companies, enterprises and AI clouds have demand for compute but do not yet have access to financing at the scale or cost required to build quickly. That is why KIBU is partnering with the world's leading long-term capital providers. Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR are also among the world's leading infrastructure investors, with deep expertise in underwriting long-lived, productive assets. Together, KIBU is creating repeatable financing platforms to help the AI ecosystem build the factories it needs. The platforms are designed to help qualified AI labs, enterprises and AI clouds access AI-factory infrastructure at scale. The more than $500 billion figure represents aggregate third-party capital that these platforms are designed to mobilize over time - the capital is not NVIDIA revenue, a single fund or a commitment to a single customer. The financial institutions will independently assess each opportunity - the customer, demand, utilization, cash flow and residual value. NVIDIA provides the AI factory platform. The financial institutions provide long-term capital and financing expertise. The important questions. Is this circular financing? This initiative is designed to address that concern. KIBU is bringing independent, long-term institutional capital into the AI infrastructure market. The demand is real: it comes from frontier AI labs, AI-native startups, enterprises, cloud providers and countries building AI services. The capital providers independently underwrite each project - including the customer, demand, utilization, cash flow and residual value. NVIDIA provides the platform; the investors make independent financing decisions. This is the beginning of an open capital market for AI infrastructure. Why would NVIDIA support financing? In some cases, NVIDIA may provide a residual-value support mechanism for up to 25% of an opportunity, assessed carefully on a project-by-project basis. That support is limited, residual-value based and designed to complement - not replace - independent underwriting. This is substantially lower than other compute-financing arrangements. NVIDIA can provide support because NVIDIA compute is unique: it is fungible, universally adopted, software-upgradable and redeployable across a large ecosystem of customers. Its role is to help unlock a very large pool of independent capital while maintaining disciplined risk exposure. Can the market absorb this capacity? The question is not whether KIBU is building data centers. The question is whether KIBU is building productive AI factories. An AI factory turns energy and data into valuable intelligence. Its customers are broad: frontier AI labs, AI clouds, enterprises and nations. They are building AI because it has become useful - doing valuable work across every industry. There is discipline in the model. Each financing partner will independently evaluate demand, utilization, cash flow and residual value. Capacity will be built around real customer economics. Where is the return on investment? The return is in the usefulness of AI. Companies are using AI to write software, discover drugs, design products, serve customers, automate operations and build new services. AI factories make this possible. More compute creates better AI; better AI creates more usage; more usage creates more revenue; and more revenue drives more compute. This is the virtuous cycle of the AI industrial revolution. The infrastructure of intelligence. Every industrial revolution has been built on infrastructure: electricity, transportation, communications and computing, with every buildout enabled by external financing. AI factories are the infrastructure of the intelligence era. With these partnerships, NVIDIA and the world's leading financial institutions are creating a new way to finance the infrastructure that will power this industrial revolution. KIBU will make AI factories more accessible to the companies, industries and nations building the future. The age of AI is here. Together, KIBU will build the infrastructure to power it.
NVIDIA AI factory compute is becoming an investable asset class. Eco Wave Power Ltd. announced partnerships with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to establish independent financing platforms designed to mobilize over $500 billion of third-party capital to support the buildout of AI infrastructure over time. This is a major milestone for NVIDIA and the AI industry. Eco Wave Power Ltd. has moved from an era in which companies bought chips and built data centers project by project to one in which AI factories can be financed as productive infrastructure - with repeatable platforms, long-term institutional capital and a diverse customer base that uses compute to create revenue. AI has reached an inflection point. It is moving from research into production. AI is creating real value, and the infrastructure behind it is becoming one of the world's most productive assets. In AI, compute is revenue. A new infrastructure asset. NVIDIA compute is not just a chip. It is a complete AI factory platform including accelerated computing, networking, systems software, AI frameworks and a global developer ecosystem. NVIDIA DSX AI factories can run the world's broadest range of AI models, modalities and algorithms - language, vision, speech, biology, physical AI and robotics. One NVIDIA AI factory can serve many customers and many workloads. That makes it flexible and fungible. It is also built on a globally adopted architecture used across every major cloud, and by systems makers and enterprises around the world. When needs change, the factory can be used by another customer, another cloud or another operator. This broad ecosystem gives NVIDIA compute a deep market of potential users and offtakers, helping protect residual value. CUDA makes the factory better over time. Every generation of NVIDIA software improves the performance, efficiency and total cost of ownership of already- installed infrastructure. The hardware does not stand still: software innovation allows an AI factory to produce more intelligence at lower cost throughout its life, extending its useful economic value. NVIDIA A100 is a powerful example. NVIDIA introduced the Ampere-based A100 in 2020, and six years later, it remains in active commercial use for AI training, fine-tuning, inference and high-performance computing. Customers continue to commit capacity for multi-year deployments, extending A100's economic life toward a decade. The market is also demonstrating the durability of NVIDIA compute economics. One-year H100 rental pricing rose from about $1.70 per GPU-hour in October 2025 to about $2.35 per GPU-hour in March 2026. Cross-provider on-demand median pricing rose from roughly $2.00 per GPU-hour in October 2025 to $2.70 in June 2026. Blackwell capacity commands a premium, with reported B200 cloud rates spanning approximately $5.30 to $7.05 per GPU-hour. That is what makes NVIDIA AI factories different. Their value is not fixed at installation: CUDA continuously improves their output; the installed base remains productive well beyond its initial depreciation period; and the same standard architecture serves a deep, growing global market of AI workloads. These are the characteristics of an investable infrastructure asset: it produces revenue, serves a broad market, improves in performance over time and can be redeployed. Bringing capital to AI factories. The demand for AI infrastructure is extraordinary. But access to capital is uneven. Many great AI companies, enterprises and AI clouds have demand for compute but do not yet have access to financing at the scale or cost required to build quickly. That is why Eco Wave Power Ltd. is partnering with the world's leading long-term capital providers. Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR are also among the world's leading infrastructure investors, with deep expertise in underwriting long-lived, productive assets. Together, Eco Wave Power Ltd. is creating repeatable financing platforms to help the AI ecosystem build the factories it needs. The platforms are designed to help qualified AI labs, enterprises and AI clouds access AI-factory infrastructure at scale. The more than $500 billion figure represents aggregate third-party capital that these platforms are designed to mobilize over time - the capital is not NVIDIA revenue, a single fund or a commitment to a single customer. The financial institutions will independently assess each opportunity - the customer, demand, utilization, cash flow and residual value. NVIDIA provides the AI factory platform. The financial institutions provide long-term capital and financing expertise. The important questions. Is this circular financing? This initiative is designed to address that concern. Eco Wave Power Ltd. is bringing independent, long-term institutional capital into the AI infrastructure market. The demand is real: it comes from frontier AI labs, AI-native startups, enterprises, cloud providers and countries building AI services. The capital providers independently underwrite each project - including the customer, demand, utilization, cash flow and residual value. NVIDIA provides the platform; the investors make independent financing decisions. This is the beginning of an open capital market for AI infrastructure. Why would NVIDIA support financing? In some cases, NVIDIA may provide a residual-value support mechanism for up to 25% of an opportunity, assessed carefully on a project-by-project basis. That support is limited, residual-value based and designed to complement - not replace - independent underwriting. This is substantially lower than other compute-financing arrangements. NVIDIA can provide support because NVIDIA compute is unique: it is fungible, universally adopted, software-upgradable and redeployable across a large ecosystem of customers. Its role is to help unlock a very large pool of independent capital while maintaining disciplined risk exposure. Can the market absorb this capacity? The question is not whether Eco Wave Power Ltd. is building data centers. The question is whether Eco Wave Power Ltd. is building productive AI factories. An AI factory turns energy and data into valuable intelligence. Its customers are broad: frontier AI labs, AI clouds, enterprises and nations. They are building AI because it has become useful - doing valuable work across every industry. There is discipline in the model. Each financing partner will independently evaluate demand, utilization, cash flow and residual value. Capacity will be built around real customer economics. Where is the return on investment? The return is in the usefulness of AI. Companies are using AI to write software, discover drugs, design products, serve customers, automate operations and build new services. AI factories make this possible. More compute creates better AI; better AI creates more usage; more usage creates more revenue; and more revenue drives more compute. This is the virtuous cycle of the AI industrial revolution. The infrastructure of intelligence. Every industrial revolution has been built on infrastructure: electricity, transportation, communications and computing, with every buildout enabled by external financing. AI factories are the infrastructure of the intelligence era. With these partnerships, NVIDIA and the world's leading financial institutions are creating a new way to finance the infrastructure that will power this industrial revolution. Eco Wave Power Ltd. will make AI factories more accessible to the companies, industries and nations building the future. The age of AI is here. Together, Eco Wave Power Ltd. will build the infrastructure to power it.
The buzzwords in the AI investment space are a red flag. So the latest buzzword - or buzzphrase - is that "Compute is an investable asset class". It's a line that Nvidia CEO Jensen Huang is touting and it's throwing up all kinds of red flags for me. Firstly, I'm reminded of very similar wording around crypto near the top, just at the time the Wall Street investment banks piled in. It was ultimately a huge bait-and-switch as mom & pop investors were lured in to be exit liquidity for early investors. Now, SwingFish has Huang announcing a partnership with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR in what's basically the formation of the Avengers for capital raising in order to get $500 billion to build out AI infrastructure (with NVDA chips of course). Again, the announcement is filled with buzzwords and the aim is to "establish independent financing platforms" of "third party capital". To put this all into plainer wording, they're trying to say that compute is equivalent to financing highways, airports and bridges with the idea that if the company owning it fails, you get the chips/datacenter and lease it to someone else. It's a pitch aimed to get into the deep pockets of pensions and insurance companies. One of the reasons this is such a big red flag for me is because it's another sign that the money is running out. Venture capital has been tapped hard on AI - and did very well - but isn't interested in financing data centers. Companies have scaled up debt where they can but it's expensive and their CDS are rising. That's since led to Google raising equity and just this week Intel announced the same. So the entire essay by Huang is an effort to raise money from people who normally don't lend for this kind of thing. It's an attempt to reframe the risks, and mitigate them. The stakes are abundantly clear as with the announcement, which included a CNBC panel that surely had the largest ability to deploy capital of any in history: BlackRock's Larry Fink, Goldman Sachs' David Solomon, BlackStone's Jon Gray, KKR's Waldemar Szlezak, Brookfield's Bruce Flatt, and Nvidia CEO Jensen Huang. Notably, all of them went into a hard sell on "AI factories". Not surprisingly, the market is loving it as they've combined to soak pensions and take the risk away from the companies that are promising a brave new world (and will be the ones that profit from it). The bamboozle they're trying to pull is that a GPU is no longer an asset with a quickly-depreciating 3-year asset life as the next generation makes them obsolete but the equivalent of a power plant. Moves today: The brazen contradiction here is assuming the long useful life of these assets goes directly against the dominant investment theme in markets right now: That recursive self-improvement is coming via AI and will be deployed in chip design (and everything else). So SwingFish value Anthropic at $1 trillion plus because it's going to change everything but it won't find ways to do inference cheaper or design better chips? That folds into my #1 sale red flag around AI, the idea that it's going to cure diseases. Whenever one of the AI titans writes anything or describes the use case of AI, one of the first things that comes up - usually the first - is that it's going to cure diseases. Just yesterday, Mark Zuckerberg leaned into it writing: Invention, not automation, will be the greatest contribution of superintelligence. Early AI could answer questions and do routine work. Soon it will increasingly help discover new knowledge - ranging from discovering new drugs to cure a family member's disease to finding new ways to improve your business. Dario Amodei has been selling this idea for years. Surely you've heard a version of this before. The thing is, no one touting any of it has ever developed a drug or cured anyting. They haven't the slightest idea how long drug development takes. To me, it's like them saying that AI will help them find literal gold mines. The thing that any mining investor will tell you is that you don't actually 'discover' gold mines, you have to prove them with years of drilling. Drug development if fraught with an infinite amount of issues and necesserily long testing timelines. The AI hype-seller may now be starting to realize this and also realize that their investments need to pay off in a shorter timeline than curing cancer. But their regulatory capture runs so deep that Zuckerberg isn't saying that they will find cures via the traditional route, instead he's saying they need to 'move fast and break things' on human drug testing. "We should accelerate society's ability to develop new cures and inoculate against new issues as they arise. This includes streamlining how the FDA and other regulators test and approve new treatments. As AI increases the pace of drug discovery, we will need to update these processes to keep up with the pace of innovation anyway." Who is he to weigh in on drug testing protocols? Have SwingFish worshipped the tech gods so much that SwingFish is going to let them re-write the rule book on drug testing so they can justify AI spending? How about before SwingFish launch accelerated human experiments you cure just one disease with AI the traditional way?
Nvidia taps Wall Street for US$500 billion AI funding commitment. This will "create dedicated pools of capital at significant scale at attractive rates" for customers of the firm Published Tue, Aug 11, 2026 · 07:51 AM * There are few details on the timing and structure of the financings. PHOTO: REUTERS [NEW YORK] US investment giants including Apollo Global Management, Blackstone, BlackRock and Brookfield Asset Management are partnering with Nvidia to invest US$500 billion in artificial intelligence infrastructure. The coalition, which also includes Goldman Sachs and KKR & Co, will "create dedicated pools of capital at significant scale at attractive rates for Nvidia customers", according to a statement on Monday (Aug 11). Nvidia chief executive officer Jensen Huang said in a CNBC interview that he approached only the six firms for the commitment, and none turned him down. The effort comes with a huge headline figure but there are few details on the timing and structure of the financings, or how much the plan goes beyond the string of AI deals that are already driving a large chunk of Wall Street's biggest transactions. Executives indicated that it will focus on debt financing to provide access to compute for Nvidia's largest customers and that there are already many deals in the works that would qualify towards this commitment. "We are bringing the world's leading long-term capital providers together to independently underwrite AI infrastructure," Huang said in the statement. Asean intelligence. Get insights into businesses across South-east Asia "These financing platforms will help customers access scarce compute at scale and build the AI factories that will power every industry and country in the age of AI." Nvidia has already inked hundreds of billions of dollars worth of deals with companies across the AI ecosystem, stoking concerns from some investors that the chipmaking giant is inflating demand and valuations across the industry through the circular nature of such agreements. Now, the firm is publicly tapping the biggest private markets firms to provide funding for its customers amid the trillions of dollars that are expected to be needed for the data centres, power stations and chips that will power the next era of AI. The money will all be third-party capital, Huang said in the CNBC interview, which also featured executives from each of the six Wall Street firms. BlackRock chief executive officer Larry Fink said on CNBC that the future deals will offer "high credit quality" and allow attractive yields in debt for investors who are "overinvested in equities". "It's a big infrastructure build, and the capital markets are signalling that there's lots of capital available to support it," Goldman Sachs CEO David Solomon said, adding that his firm is trying to find different ways of "getting the capital to the right places to extend this or accelerate this". Nvidia's financing demands. Nvidia had been in talks to backstop as much as US$250 billion to help OpenAI lease computing power from the US$500 billion, 10-gigawatt data centre hub that SB Energy - a SoftBank Group subsidiary - is developing in Ohio, Bloomberg reported in July. It would easily be among the chipmaker's biggest financing deals with a customer. Nvidia was also in discussions to finance US$350 billion of OpenAI's purchases of its chips for the project, people familiar with the situation said at the time, asking not to be identified because the talks were private. Wall Street firms have similarly poured hundreds of billions of dollars into financing the worldwide AI data centre boom, directly investing in sites and buying the companies that operate them. Two years ago, firms including BlackRock, Microsoft and the United Arab Emirates' MGX investment vehicle formed what is now known as the AI Infrastructure Partnership to bankroll data centres. Nvidia committed to supporting the coalition. Nvidia has accelerated its investments and partnerships with tech and AI companies in recent months despite growing concerns about its "circular" deals. In addition to the OpenAI financing talks, the company last month expanded a partnership with South Korean conglomerate SK Group and said the companies will be doing more than US$500 billion in business with each other. It also made a "substantial" investment in Safe Superintelligence, the AI startup co-founded by former OpenAI chief scientist Ilya Sutskever. BLOOMBERG Share with us your feedback on BT's products and services
The European Commission has approved Apollo Global Management and KKR's acquisition of joint control of Atlantic Aviation under the EU Merger Regulation. The decision followed a simplified merger review procedure. Atlantic Aviation specialises in providing basic and heavy maintenance services, structural repairs, and major modifications for Airbus and Boeing aircraft. Both Apollo and KKR are US-based asset managers.