Mid Level AI Platform Engineer Jobs
Mid level ai platform engineer jobs go to engineers ready to own platform components end to end, drive architectural decisions with limited oversight, and mentor earlier-career teammates. Roles are concentrated across Technology & Software, Banking & Financial Services, and Consulting & Professional Services, with a strong mix of remote, hybrid, and on-site positions, and employers like Databricks, JPMorganChase, and Capital One hiring at this level now.
Find JobsOverview
Showing 5 of 136+ Mid Level AI Platform Engineer jobs
Our team builds the secure identity and transparency services that anchor those guarantees, for Apple Intelligence and PCC, iMessage, and other critical Apple products. We produce the backend systems behind the cryptographic proof, so the billions of Apple users and their devices can connect and compute with confidence.
We are a small team with big impact, tackling challenges across verifiable key transparency, privacy-preserving infrastructure, data consistency and reliability at extreme scale, and publicly auditable, tamper-evident logging systems that span an increasingly diverse cloud footprint.
Are you interested in product innovation and building services with unrivaled privacy and security, while solving unique, large-scale, and highly-complex technical problems? Are you passionate about delivering the best possible experience to customers? If so, come join us!
Description
Join us to build the transparency infrastructure that makes private AI possible, and that scales to the next billion users and devices. Your responsibilities will cover all aspects of the software development lifecycle, including feature exploration, architectural design, development, testing, and operations for services that demand the highest standards of reliability and security. You will represent our team in various cross-functional settings and lead projects in our realms of expertise.
We are seeking a strong technical, hands-on engineer who is passionate about applying their skills to create real-world impact and build products that users love. You should feel a personal stake in the services we are responsible for, be eager to learn about new technologies, and have the ability to build positive and effective relationships with the people you work with.
Our work is complex, challenging, and highly visible: as Apple Intelligence grows, transparency becomes load-bearing infrastructure for AI privacy at global scale. The opportunities for you to make an impact here are boundless.
","responsibilities":"* Design, build, and operate the critical server-side components that power new communication features, taking full ownership of their architecture, quality, and reliability.
- Act as the server-side technical lead for new features, partnering with iOS, hardware, and other service teams to influence and craft the end-to-end architecture.
Assume responsibility for the successful delivery of a feature’s backend, while acting as a key collaborator in the success of the overall feature across all layers of the stack.
Lead sophisticated, multi-functional projects from conception to delivery, ensuring technical alignment and flawless integration between your services and other components.
Mentor and guide engineers both within our team and across the company, helping to develop their skills and encouraging a culture of technical perfection and collaboration.
Uphold and champion our deep dedication to user experience, privacy, and security in every aspect of your work.
Preferred Qualifications
Good understanding of multi-threading, non-blocking I/O, and client-server development.
Experience with applied cryptography
Understanding of transparency systems (key transparency, certificate transparency, Merkle trees)
Experience with distributed database systems (such as Cassandra)
Minimum Qualifications
At least 3+ years of backend software engineering experience
Experience in Java, Go, C#, or similar languages.
Experience in building large scale, highly available application services.
Independent, driven, motivated, and a deep sense of ownership
Strong written and verbal communication skills
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $171,600 and $302,200, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
See All 136+ Mid Level AI Platform Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsMid Level AI Platform Engineer Job Market
Who's Hiring
- Databricks7
- JPMorganChase5
- Capital One4
- The Hartford4
- Booz Allen Hamilton4
Top Industries Hiring
- Technology & Software44
- Banking & Financial Services17
- Consulting & Professional Services17
- Insurance10
- Electronics & Hardware9
Mid Level AI Platform Engineer Jobs: Frequently Asked Questions
How do I get a mid level ai platform engineer job?
Position yourself around ownership, not just contribution. Highlight projects where you made independent technical decisions, improved platform reliability or scale, or delivered features end to end without close supervision. Concrete outcomes matter more than titles: quantify throughput gains, latency improvements, or infrastructure cost reductions. A focused portfolio showing real system design choices signals readiness for this level far better than a long list of tools.
Which companies hire mid level ai platform engineers?
Companies hiring mid level ai platform engineers right now include Databricks, JPMorganChase, and Capital One, based on current listings on Migrate Mate as of July 2026. Hiring at this level comes from a broad mix of technology firms, financial services companies, and large enterprises that are actively building or scaling internal AI infrastructure.
Are there remote mid level ai platform engineer jobs?
Yes, remote and hybrid options are common at this level. About 42% of mid level ai platform engineer openings are remote or hybrid as of July 2026, reflecting strong employer demand for experienced engineers who can work independently across distributed teams. On-site roles tend to cluster at companies with strict data security or on-premises infrastructure requirements.
How do I move up to a mid level ai platform engineer role?
The path from entry level to mid level is built on accumulated ownership. Early-career engineers grow into this tier by taking end-to-end responsibility for platform features, deepening expertise in areas like ML infrastructure, orchestration, or data pipelines, and demonstrating measurable impact on system performance or team productivity. Consistent delivery on complex tasks, combined with some cross-functional collaboration, is what distinguishes a mid level candidate from a junior contributor.
Which industries hire the most mid level ai platform engineers?
Mid Level ai platform engineer roles concentrate in Technology & Software, Banking & Financial Services, and Consulting & Professional Services, based on current listings on Migrate Mate as of July 2026. These sectors invest heavily in AI platform infrastructure to support product development, operational automation, and data-driven decision-making at scale, which drives sustained demand for engineers who can operate with meaningful autonomy.