cloud infrastructure engineer

Cisco

The application window is expected to close on: 09/11/2026Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.
 
Meet the Team
 The Platform Engineering organization is responsible for building and operating the foundational cloud-native platforms that power engineering across Cisco Network Platform. Our team owns the Kubernetes ecosystem used by thousands of developers, spanning hundreds of clusters across public and on-premise environments.. We provide the infrastructure, automation, observability, security, and self-service capabilities that enable product teams to build and operate services reliably at scale.
 We are a highly collaborative team of SREs, who enjoy solving complex distributed systems challenges. Our culture emphasizes ownership, operational excellence, automation, and continuous improvement. This is an opportunity to shape the future of Kubernetes and platform engineering within Cisco Network Platform while influencing the experience of engineers across the company.
 Your Impact
 Architect and drive the evolution of Kubernetes platform strategy across cloud and on-premises environments supporting mission-critical workloads at scale.
 Lead the design and implementation of platform capabilities that improve reliability, security, scalability, and developer productivity for hundreds of engineering teams.
 Partner with engineering, security, and product leaders to define multi-year platform roadmaps and drive execution of company-critical initiatives.
 Provide technical leadership during major incidents, architecture reviews, platform transformations, and strategic infrastructure investments.
 Mentor senior engineers and help raise the engineering bar through technical leadership, design reviews, operational excellence, and architectural guidance.
 
Minimum Qualifications
 
<ul>
<li>15+ years of experience designing, building, and operating large-scale distributed systems in production environments.</li>
<li>7+ years of hands-on experience operating Kubernetes platforms in production, including multi-cluster environments.</li>
<li>Experience architecting and operating cloud-native infrastructure across AWS, Azure, GCP, or hybrid cloud environments.</li>
<li>Experience designing, operating, and troubleshooting networking architectures for large-scale Kubernetes platforms, including CNI implementations, ingress and egress traffic management, service-to-service communication, multi-cluster connectivity, and network observability.</li>
<li>Experience with Infrastructure-as-Code and GitOps technologies, including Terraform and ArgoCD or equivalent platforms.</li>
<li>Strong communication and leadership skills with the ability to effectively influence engineers, architects, senior leaders, and executive stakeholders.</li>
<li>Proven track record leading cross-organizational platform initiatives and influencing technical strategy across multiple engineering teams.</li>
<li>Experience implementing SRE practices, including SLOs, incident management, production readiness reviews, and operational excellence programs.</li>
<li>Strong software engineering experience with Go, Python, or similar programming languages used for automation and platform development.</li>
</ul>
Preferred Qualifications
 
<ul>
<li>Experience with migrating monolithic applications to a microservices architecture.</li>
<li>Knowledge of networking (i.e. switching, routing, wifi, IoT).</li>
</ul>
Why Cisco?
 
At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.
 Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.
 We are Cisco, and our power starts with you.
 
Message to applicants applying to work in the U.S. and/or Canada:
 
The starting salary range posted for this position is $231,400.00 to $331,800.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.
 Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process.
 
U.S. employees are offered benefits, subject to Cisco’s plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time.
 
U.S. employees are eligible for paid time away as described below, subject to Cisco’s policies:
 
<ul>
<li>10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees</li>
<li>1 paid day off for employee’s birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco</li>
<li>Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees</li>
<li>Exempt employees participate in Cisco’s flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)</li>
<li>80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next</li>
<li>Additional paid time away may be requested to deal with critical or emergency issues for family members</li>
<li>Optional 10 paid days per full calendar year to volunteer</li>
</ul>
For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco’s policies.
 
Employees on sales plans earn performance-based incentive pay on top of their base salary, which is split between quota and non-quota components, subject to the applicable Cisco plan. For quota-based incentive pay, Cisco typically pays as follows:
 
<ul>
<li>.75% of incentive target for each 1% of revenue attainment up to 50% of quota;</li>
<li>1.5% of incentive target for each 1% of attainment between 50% and 75%;</li>
<li>1% of incentive target for each 1% of attainment between 75% and 100%; and</li>
<li>Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation.</li>
</ul>
For non-quota-based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid.
 
The applicable full salary ranges for this position, by specific state, are listed below:
 
New York City Metro Area: 
$231,400.00 - $381,600.00
 
Non-Metro New York state& Washington state: 
$222,900.00 - $343,600.00
 <ul>
<li>For quota-based sales roles on Cisco’s sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined.</li>
</ul>
** Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements.

Principal Engineer - Platform Engineering

Vast

<div><h1 class="jobSectionHeader">Developer Experience Engineer</h1>
Vast.ai &middot; Los Angeles or San Francisco Bay Area<h3 class="jobSectionHeader">
About Us</h3>
Vast.ai&rsquo;s cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing&mdash;reshaping our future for the benefit of humanity.
We are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out‑sized, and leadership is earned by shipping excellence.
We seek engineers with strong intrinsic drive, a true passion for advancing the state of the art, and a mix of architecture, coding, and communication skills.
We've never had a dedicated role focused on the developers who build on Vast: the people renting compute from us to train and ship their models. That's what we're hiring for. You'll be our first DevEx Engineer, and you'll own the experience of building on Vast: the reference implementations and example code developers copy, and how we show up in the community around them.<h2 class="jobSectionHeader"> 
Why now</h2>
There's already an active community around Vast in our Discord, on Reddit, on X, and in YouTube comments. Some of it is the builders you'll serve; some of it is hosts and noise. Nobody on our side is really in there today, and our competitors staff this heavily. So part of the job is showing up for the developers who are already here, and part of it is growing the right audience around them. 
 
What you'll own<ul><li>
Technical content. Tutorials, example repos, and short videos that show people how to get something running on Vast. The useful kind that developers pass around on their own.</li><li>
Product feedback. You'll hear what's broken before anyone else does. Get it back to the product team, clearly and often.</li><li>
Events. Run our presence at hackathons (we already have sponsorships lined up), meetups, and conferences, including getting on a plane and showing up in person.</li><li>
Community. Be a real presence in our Discord, on Reddit, and on X. Answer the actual technical questions people ask, the kind they post at 1am when a container won't start. Set the tone for how Vast talks to developers.</li><li>
Creator partnerships. Work with developer-focused YouTubers and other creators, the ones with real audiences rather than bought ones.</li></ul> 
What you won't own
To be straight about scope: this role doesn't cover paid ads, brand and positioning strategy, or the growth dashboard. It's also focused on the demand side, the developers who build on Vast, not our GPU hosts and suppliers, who have their own very different needs. Other people own all of that and you'll partner with them. We want your time going into the builder community and the content that serves it, because that's where it pays off. 
 
Who you are<ul><li>
You've been an engineer. You can deploy a model and debug someone's setup, and developers can tell you've done the work yourself. This part can't be faked.</li><li>
You've built a developer community before, ideally close to from scratch. You know what makes one grow and what quietly kills it.</li><li>
You like people more than most engineers do. Writing, posting, talking, showing up at events. That's the actual day-to-day.</li><li>
You run yourself. Nobody's going to hand you a content calendar, and you'd rather ship something than sit in a planning meeting about it.</li></ul> 
Nice to have<ul><li>
Time at a cloud, GPU, AI-infrastructure, or developer-tools company.</li><li>
Something you've made that traveled: a tutorial series people reference, a repo with real stars, a talk that got passed around.</li><li>
Working knowledge of the AI/ML stack: model deployment, inference, fine-tuning.</li></ul> 
Your first 90 days<ul><li>
Get a steady, regular presence going on Reddit and Discord.</li><li>
Ship your first batch of tutorials and example repos.</li><li>
Represent Vast at a hackathon we're already sponsoring this summer.</li><li>
Give us a clear read on how other GPU and AI-infra companies show up with developers, and where we're behind.</li></ul> 
Compensation and location
$160,000&ndash;$200,000 base depending on experience, plus equity. We're profitable, venture-backed, and growing, so the equity is a stake in a real company with a real valuation, not a lottery ticket. Los Angeles or San Francisco Bay Area. Travel and conference budget covered.<h3 class="jobSectionHeader">
Benefits</h3><ul><li>
Comprehensive health, dental, vision, and life insurance</li><li>
401(k) with company match</li><li>
Meaningful early-stage equity</li><li>
Onsite meals, snacks, and close collaboration with founders/tech leaders</li><li>
Ambitious, fast-paced startup culture where initiative is rewarded</li></ul>
Compensation Range: $160K - $200K</div>

Developer Experience Engineer

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Amazon Interactive Video Service (Amazon IVS) is AWS's fully managed live streaming service, built on the same battle-tested technology that powers Twitch and trusted by thousands of enterprises across gaming, social, live commerce, sports, and entertainment. 
 
Our mission: enable developers to build communities around live video. We handle everything from ingest to processing to delivery at global scale, so developers can focus on creating interactive, engaging live experiences for their audiences. Whether you're streaming to tens of millions of concurrent viewers or just getting started, Amazon IVS removes the complexity so developers can move fast. 
 
As a Software Dev Engineer on the IVS's Data team, you will be responsible for empowering internal teams and IVS customers with the data they need to make key operational and business decisions. We operate petabyte-scale data infrastructure for collecting, processing, and warehousing IVS data. We support streaming and batch pipelines to facilitate analytics, reporting, and ML workloads. We offer analytics tools and data products designed to make it easy and fast for our customers to extract the insights they need from their data. 
 
Key job responsibilities 
<ul><li>Design, implement, and maintain scalable data infrastructure in native AWS</li><li>Build and optimize data pipelines (batch and streaming) to support analytics, reporting, and ML workloads</li><li>Ensure data quality, reliability, and observability through monitoring, logging, and automated alerting</li><li>Work closely with product and analytics teams to understand requirements and deliver high-performance solutions</li><li>Champion best practices for security, compliance, and governance in data infrastructure</li><li>Identify opportunities to optimize performance and cost of data platforms</li><li>Stay current with emerging tools, frameworks, and cloud services in the data infrastructure ecosystem</li></ul> 
A day in the life 
Your primary focus will be empowering customers to succeed with their data by ensuring they can: 
<ul><li>Gather and access data at scale &ndash; Enable seamless data collection and retrieval that grows with their needs</li><li>Extract meaningful insights &ndash; Provide the right tools and capabilities to uncover the answers they're seeking</li><li>Trust their data &ndash; Maintain confidence in the completeness, accuracy, and reliability of their information</li></ul>
Achieving these goals requires close collaboration and strong partnerships with Product and Data Science teams to deliver solutions that truly meet customer needs. 
 
About the team 
Amazon Interactive Video Service (Amazon IVS) is a managed live streaming solution from AWS that enables low-latency and real-time video experiences for millions of viewers worldwide. We power engaging live experiences for some of the largest customers in the live video space and continuously push the boundaries of what&rsquo;s possible with interactive video technology.</div><h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</h2><ul><li>3+ years of non-internship professional software development experience</li><li>2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>1+ years of software development engineer or related occupational experience</li><li>1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience</li><li>1+ years of Object Oriented Design experience</li><li>Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field</li><li>Experience programming with at least one software programming language</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>Bachelor's degree in computer science or equivalent</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, San Francisco - 165,200.00 - 223,600.00 USD annually 
USA, WA, Seattle - 143,700.00 - 194,400.00 USD annually</div>

Software Dev Engineer II, Amazon Interactive Video Service (IVS)

Smvsoft LLC

Founding Engineer - Applied AI San francisco, CA (Full time)- In-Office$180k-$230k per annumNO C2CAbout the RoleHiring a world-class Applied AI Engineer to build the core systems behind their automation engine for hardware engineering.This is a deeply technical, high-impact role. You will be among the first technical hires and will own mission-critical systems end-to-end. The problems are ambiguous, the constraints are real, and the expectations are high. If you move fast from idea to production, care deeply about customer experience, and want to build foundational AI infrastructure for the world's most impactful industries, this role is for you.Key Responsibilities<ul><li>Design and implement core workflows and infrastructure for hardware engineering agents, including intelligent context management, novel indexing approaches, and post-training</li><li>Build agents and ML models that can interpret, reason over, and manipulate complex engineering design data, integrating with enterprise-grade engineering tools and systems</li><li>Work closely with customers and the engineering team to deliver AI-powered workflows that are reliable, intuitive, and trusted in production environments</li><li>Prototype rapidly, validate ideas with real users, and ship frequently</li><li>Influence engineering culture, architecture decisions, and the future of the product</li></ul>RequirementsMust-Have<ul><li>Bachelor's or higher in Computer Science, Machine Learning, or equivalent experience</li><li>Strong familiarity with LLM architectures and agent research trends</li><li>Excellent programming skills with experience using ML libraries such as PyTorch, Hugging Face, and W&amp;B</li><li>Experience building production ML or AI systems</li><li>Solid practical experience with search and information retrieval</li><li>Moves fast from idea to production, with a genuine care for customer experience</li><li>Based in or willing to relocate to San Francisco, or an exceptional remote candidate</li></ul>Nice-to-Have<ul><li>2+ years in applied machine learning, backend engineering, or AI infrastructure</li><li>Experience working with machine learning over geometric data, including CAD</li><li>Track record of high-impact contributions or published papers at top-tier AI labs or teams</li></ul>Pay: $180,000.00 - $230,000.00 per yearWork Location: In person

Founding Engineer - Applied AI

Instabase

<div><div>At Instabase, we're passionate about democratizing access to cutting-edge AI innovation to enable any organization to solve previously unsolvable unstructured data problems in their industry. With customers representing some of the largest and most complex organizations in the world, and investors like Greylock, Andreessen Horowitz, and Index Ventures, our market opportunity is near infinite.

Instabase offers a consumption-based pricing model where customers can pay only for what they use, aligning directly with the value our products deliver. It empowers our clients to explore our AI Hub platform features extensively, enabling them to uncover crucial business insights. This customer-centric model allows Instabase to glean insights from diverse use cases and behaviors, ensuring we deliver top-tier solutions that provide unmatched advantages for everyday business operations.

With offices in San Francisco and Bengaluru, Instabase is a truly global company. We are people-first, and we've built a fearlessly experimental, endlessly curious, customer obsessed team who work together and help organizations around the world turn their unstructured data into insights instantly.</div><h1 class="jobSectionHeader">
Technical Lead Manager (TLM) &mdash; AI Systems &amp; Agents</h1>
<h2 class="jobSectionHeader">About Instabase and the Evolution of Our Business Model</h2>

Instabase is the pioneer in helping the world's largest enterprises&mdash;including global banks, insurance leaders, and healthcare giants&mdash;unlock and automate value from unstructured data. Our core platform is the industry standard for reading, understanding, and processing complex, unstructured documents at massive scale.

As a strategic addition to our current business model, we are building SuperApp, our natively multimodal, stateful AI assistant and autonomous agent platform. SuperApp represents the next evolution of Instabase: moving from passive document extraction to active, self-correcting agentic execution. By combining our enterprise-grade document understanding with secure, real-time sandboxed code execution, SuperApp enables users to not only parse unstructured data but programmatically act on it, write and run execution scripts, orchestrate complex software tools over Model Context Protocol (MCP), and complete open-ended reasoning tasks in a secure environment.

To lead the engineering team behind this next-generation capability, we are seeking an elite, hands-on Technical Lead Manager (TLM) &mdash; AI Systems &amp; Agents.
<h2 class="jobSectionHeader">
The Role: Player-Coach Leadership</h2>

This is an high-impact, low-bureaucracy role designed for a world-class systems engineer and builder. We keep our teams intentionally lean and fast. You will serve as a Player-Coach leading a tight, elite squad of 3 to 5 AI systems engineers.

At Instabase, we believe managers of small teams should stay close to the metal. Your time will be split:
<ul>
<li>60% to 70% Hands-on Engineering: Actively designing multi-turn agent loops, writing production code, building secure sandboxing environments, and architecting systems.</li>
<li>30% to 40% Leadership &amp; Mentorship: Recruiting top-tier talent, mentoring engineers, reviewing PRs, and aligning product roadmaps with technical execution.</li>
</ul><h2 class="jobSectionHeader">What You Will Do</h2>
<ul><li>Architect Stateful Agent Loops: Design and implement highly reliable, multi-turn agentic planning and execution state machines capable of self-correction, tool orchestration, and long-context memory persistence.</li>
<li>Build Secure Execution Sandboxes: Own the runtime execution layer where model-generated code (such as Python data-analysis scripts) is safely isolated, monitored, and run in real-time without compromising enterprise security boundaries.</li>
<li>Pioneer Tool Orchestration &amp; MCP: Expand our agent capabilities by designing composable tool-calling integrations using Model Context Protocol (MCP) and custom API interfaces.</li>
<li>Build Evaluation &amp; Trajectory Testing Harnesses: Establish programmatic frameworks (using LLM-as-a-judge and trajectory evaluations) to test if agent loops, tool-calling selections, and error recoveries behave safely and deterministically.</li>
<li>Scale High-Performance Systems: Work on deep systems problems including latency optimization, semantic caching, speculative execution, and streaming intermediate agent states for a responsive user experience.</li>
<li>Scale the Team: Bootstrap, hire, and mentor a small, elite, high-velocity team of software and AI engineers.</li>
</ul><h2 class="jobSectionHeader">Our Technical Stack</h2>
<ul><li>Orchestration &amp; Frameworks: LangGraph, LangChain, Go/Python, React, Node, Next.js.</li>
<li>Infrastructure &amp; Security: Secure sandboxed runtimes (Docker, gVisor, WebAssembly), GCP, AWS, Kubernetes, Cloud SQL (PostgreSQL, TimescaleDB), Redis, Pub/Sub.</li>
<li>AI &amp; Models: Integration with advanced reasoning models (GPT-4o, o3, Claude 3.5 Sonnet, DeepSeek) across custom function-calling, LLM fine-tuning, and hybrid vector-search RAG pipelines.</li>
<li>Standards: Model Context Protocol (MCP) tool schemas and APIs.</li>
</ul><h2 class="jobSectionHeader">About You</h2>
<ul><li>8+ Years of Professional Engineering Experience: A strong, proven background in software engineering, with significant tenure building and scaling backend systems, infrastructure, or platform services.</li>
<li>Active LLM &amp; Agentic Engineering Experience: Practical, hands-on experience building production-grade LLM applications, multi-agent workflows (using DAGs or state machines), or tool-calling executors.</li>
<li>Systems &amp; Infrastructure Rigor: Deep familiarity with building secure sandboxed runtimes, container isolation, API platforms, caching strategies, or high-throughput real-time data streaming.</li>
<li>Small-Team Leadership Experience: Proven track record of mentoring senior engineers, driving technical design reviews, and leading high-velocity squads as a Tech Lead, TLM, or hands-on EM.</li>
<li>An Active Builder: You love writing code. You are excited about the prospect of coding daily and staying out of the meetings and administrative bloat of traditional big-tech management.</li>
<li>Educational Background: BS, MS, or Ph.D. in Computer Science, Computer Engineering, or a highly quantitative field.</li>
</ul>
Compensation: The base salary range for this role is $230,00 to $270,000 + bonus, equity, and benefits. The actual pay may vary based on factors such as location, experience, and skills.
<div>
<div>US Benefits:</div>
<ul><li>Flexible PTO: Because life is better when you actually live it!</li>
<li>Comprehensive Coverage: Top-notch medical, dental, and vision insurance.</li>
<li>401(k) with Matching: We've got your back for a secure future.</li>
<li>Parental Leave &amp; Fertility Benefits: Supporting you in growing your family, your way.</li>
<li>Therapy Sessions Covered: Mental health matters&mdash; 10 free sessions through Samata Health.</li>
<li>Wellness Stipend: For gym memberships, fitness tech, or whatever keeps you thriving.</li>
<li>Lunch on Us: Enjoy a lunch credit when you're in the office.</li>
</ul>
#Li-Hybrid</div><div> 

</div><div>Instabase is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status. Research shows that in order to apply for a job, women feel they need to meet 100% of the criteria while men usually apply after meeting about 60%. Regardless of how you identify, if you believe you can do the job and are a good match, we encourage you to apply.</div></div>

Technical Lead Manager

Hellyeah AI

AI Engineer - Learn Engine: Intelligence &amp; OptimizationLocation: San Francisco HQ; ShanghaiAddress: San Francisco, CaliforniaEmployment Type: Full timeLocation Type: HybridDepartment: EngineeringCompensation: San Francisco $200K - $1M + 0.5% - 3% equityBuild the brain of an autonomous growth OS. The system you create will manage millions in ad spend and get measurably smarter with every dollar. This is the moat: every competitor has humans optimizing campaigns manually. You are building the intelligence layer that compounds. The Platform engineer creates the tools; you create the decisions. Together you build something nobody else has.Must Have- Has built recommendation, optimization, or decision systems where outputs improve future inputs.- Strong statistical reasoning and experimentation judgment under noisy real-world data.- Strong LLM orchestration or agent-system experience for reasoning over campaign context.- Can design optimization policies, scoring systems, or automated recommendation loops.- AI-first development workflow and ability to ship production systems quickly.Nice to Have- Ad-tech optimization patterns: bid management, budget allocation, ROAS optimization.- Reinforcement learning experience.- Hyperparameter optimization experience.- Model fine-tuning experience.- Experience building agent-driven automation where LLM agents take actions.- Background in growth engineering, performance marketing, or data science.- Experience with Mastra or similar agent orchestration framework.What You Will OwnOwn the intelligence and optimization layer of Learn Engine. Build recommendation engines for bid changes, budget reallocation, pause/boost decisions, and postback optimization. Turn SSOT campaign data into high-quality optimization guidance and closed-loop decision systems. Define how the system learns from outcomes and continuously improves campaign strategy over time. This role owns decision quality, optimization policy, and learning loops, not platform plumbing or simulator infrastructure.Pay: $200,000.00 - $1,000,000.00 per yearWork Location: In person

AI Engineer - Learn Engine: Intelligence & Optimization

Ontrac Solutions

<div><h1 class="jobSectionHeader">Overview</h1>
We are seeking a Principal GenAI Architect / Forward Deployed Principal Engineer to lead the design, delivery, and productionization of enterprise-grade Generative AI solutions within a highly regulated banking environment. This role will partner directly with business, product, engineering, architecture, risk, cyber, legal, compliance, and model governance teams to translate high-impact financial services use cases into scalable, secure, and compliant AI systems.
The ideal candidate has deep experience designing and delivering production-scale GenAI solutions across enterprise environments, with strong exposure to banking, financial services, risk management, customer operations, regulatory controls, and data protection requirements. This person will serve as a recognized GenAI expert across the organization, helping define reusable patterns, influence platform roadmaps, and raise the technical bar for responsible AI adoption across lines of business.
<h2 class="jobSectionHeader">Key Responsibilities</h2>
<h3 class="jobSectionHeader">GenAI Architecture &amp; Production Readiness</h3>
Own and define enterprise-grade GenAI architectures for banking and financial services use cases, including RAG pipelines, agentic workflows, prompt orchestration, and multi-model routing strategies.
Drive production readiness for GenAI solutions, ensuring scalability, resiliency, observability, latency optimization, security, and cost efficiency.
Lead complex architectural decisions across data ingestion, vector databases, model selection, guardrails, API scalability, performance optimization, and secure integration with banking systems.
Establish reference architectures, reusable patterns, and best practices to accelerate responsible GenAI adoption across lines of business.
Partner with central AI platform teams to align solution architecture with enterprise AI services, platform capabilities, banking technology standards, and long-term roadmap priorities.
<h3 class="jobSectionHeader">Banking Use-Case Delivery</h3>
Act as a Forward Deployed Principal Engineer, partnering directly with business, product, and engineering teams to deliver high-impact GenAI use cases from ideation through production.
Translate banking and financial services business problems into clear AI system designs, technical requirements, and non-functional requirements with measurable outcomes.
Support GenAI use cases across areas such as customer service, operations, knowledge management, risk, compliance, fraud, employee productivity, document intelligence, and internal workflow automation.
Troubleshoot and resolve complex issues across non-production and production environments.
Partner closely with application teams to ensure AI solutions integrate effectively into existing banking platforms, enterprise workflows, data environments, APIs, and control frameworks.
Influence platform roadmap by feeding real-world banking use-case requirements back into central AI services and enterprise AI platform teams.
<h3 class="jobSectionHeader">Governance, Risk &amp; Compliance</h3>
Ensure all AI solutions align with banking risk, cyber, model governance, data protection, privacy, and regulatory expectations.
Partner with Cyber, Model Risk Management, Legal, Compliance, Risk, and Data Governance teams to design compliant AI patterns without slowing delivery.
Embed security, privacy, responsible AI, ethical AI, explainability, human oversight, and auditability into solution design by default.
Help define practical implementation patterns that balance innovation, speed, governance, regulatory expectations, and enterprise control requirements.
Ensure GenAI solutions are designed with appropriate guardrails for sensitive financial data, customer information, personally identifiable information, and regulated business processes.
<h3 class="jobSectionHeader">Organizational Influence &amp; Mentorship</h3>
Serve as a recognized GenAI expert across the enterprise, regularly consulted by engineering, architecture, product, risk, compliance, and leadership teams.
Mentor senior and staff-level engineers and help raise the technical bar across banking technology teams.
Contribute to internal communities of practice, architecture reviews, executive-level technical discussions, AI governance forums, and knowledge-sharing sessions.
Represent enterprise GenAI capabilities in internal innovation forums, banking technology discussions, and responsible AI showcases.
<h2 class="jobSectionHeader">Required Qualifications</h2>
7+ years of software engineering experience, with significant depth in AI/ML, data-intensive systems, distributed systems, or enterprise-scale platforms.
2+ years of hands-on Python programming experience.
2+ years of experience designing and delivering production-scale Generative AI systems in an enterprise environment.
2+ years of experience with LLMs, prompt engineering, and RAG architecture.
2+ years of experience with vector databases, semantic search, and retrieval systems.
2+ years of experience with API-driven, cloud-native architectures.
2+ years of experience with distributed systems, performance optimization, scalability, and reliability engineering.
Experience working within banking, financial services, fintech, or another highly regulated enterprise environment.
<h2 class="jobSectionHeader">Preferred Qualifications</h2>
Strong understanding of banking technology environments and non-functional requirements, including security, scalability, resiliency, observability, latency, auditability, and cost management.
Demonstrated Principal-level impact, with influence across multiple teams, platforms, business units, or lines of business.
Experience operating in highly regulated environments, with financial services or banking experience strongly preferred.
Hands-on experience with agentic AI frameworks, AI workflow orchestration, and multi-model routing.
Prior experience in a Forward Deployed Engineer, embedded engineering, or business-facing technical delivery model.
Experience partnering with risk, cyber, legal, compliance, data governance, or model governance teams to deliver production AI solutions.
Familiarity with banking controls, customer data protection, model risk management, audit requirements, regulatory expectations, and responsible AI principles.
Ability to communicate complex technical concepts clearly to senior executives, technical stakeholders, risk partners, compliance teams, and non-technical business leaders.
<h2 class="jobSectionHeader">Ideal Candidate Profile</h2>
The ideal candidate is a hands-on Principal-level engineer and architect who can move seamlessly between strategy, architecture, and execution in a banking environment. They are comfortable working directly with business teams to understand real-world financial services problems, while also going deep with engineering teams on system design, performance, security, governance, and production readiness.
This person brings strong technical judgment, enterprise banking delivery experience, and the ability to build practical, compliant GenAI solutions that can scale responsibly across a large financial institution.</div>

Principal AI Engineer

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