About Airwallex Airwallex is the only unified payments and financial platform for global businesses. Powered by our unique combination of proprietary infrastructure and software, we empower over 200,000 businesses worldwide - including Brex, Rippling, Navan, Qantas, SHEIN and many more - with fully integrated solutions to manage everything from business accounts, payments, spend management and treasury, to embedded finance at a global scale. Proudly founded in Melbourne, we have a team of over 2,000 of the brightest and most innovative people in tech across 26 offices around the globe. Valued at US$8 billion and backed by world-leading investors including T. Rowe Price, Visa, Mastercard, Robinhood Ventures, Sequoia, Salesforce Ventures, DST Global, and Lone Pine Capital, Airwallex is leading the charge in building the global payments and financial platform of the future. If you're ready to do the most ambitious work of your career, join us. Attributes We Value We hire successful builders with founder-like energy who want real impact, accelerated learning, and true ownership. You bring strong role-related expertise and sharp thinking, and you're motivated by our mission and operating principles. You move fast with good judgment, dig deep with curiosity, and make decisions from first principles, balancing speed and rigor. You're humble and collaborative; turn zero-to-one ideas into real products, and you "get stuff done" end-to-end. You use AI to work smarter and solve problems faster. Here, you'll tackle complex, high-visibility problems with exceptional teammates and grow your career as we build the future of global banking. If that sounds like you, let's build what's next. About the Team This team is building production AI that eliminates financial busywork for startups globally. We're delivering intelligent automation across payments, payroll, bookkeeping, and tax-freeing founders to focus on building their companies instead of managing finances. We leverage cutting-edge AI tooling across the spectrum: from prompt engineering and in-context learning to fine-tuned models and agentic systems, choosing the right approach for each problem. We work backward from real founder pain points, own customer outcomes, and ship fast. The team is small, elite, and builder-focused, led by operators with a track record of shipping AI products at scale. You'll solve hard technical problems with real autonomy and direct customer impact. About the Role You'll be a core builder in our AI team, designing and deploying intelligent systems that automate complex, multi-step workflows. You'll leverage agentic frameworks, advanced orchestration, and pragmatic model selection to take ideas from whiteboard to production. What You'll Do - Architect and deploy AI agents using frameworks like LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, and emerging OSS stacks. - Apply the right techniques across the AI spectrum - prompting, RAG, fine-tuning, or training from scratch. - Design and optimize agent architectures for reasoning, tool use, and workflow automation. - Build systems that improve with usage, creating compounding AI flywheels. - Work with backend and frontend engineers to integrate AI reasoning into secure, production systems. What You Need to Have - 2+ years in applied AI/ML engineering with production deployments. - Strong Python skills and experience with ML frameworks (PyTorch, JAX, TensorFlow). - Track record of building and deploying AI agents, orchestration frameworks, or multi-step reasoning systems. - Understanding of monitoring, evaluation, and iteration in production AI systems. - Ability to balance innovation with reliability, scalability, and compliance. Applicant Safety Policy: Fraud and Third-Party Recruiters To protect you from recruitment scams, please be aware that Airwallex will not ask for bank details, sensitive ID numbers (i.e. passport), or any form of payment during the application or interview process. All official communication will come from an @airwallex.com email address. Please apply only through careers.airwallex.com or our official LinkedIn page. Airwallex does not accept unsolicited resumes from search firms/recruiters. Airwallex will not pay any fees to search firms/recruiters if a candidate is submitted by a search firm/recruiter unless an agreement has been entered into with respect to specific open position(s). Search firms/recruiters submitting resumes to Airwallex on an unsolicited basis shall be deemed to accept this condition, regardless of any other provision to the contrary. Equal opportunity Airwallex is proud to be an equal opportunity employer. We value diversity and anyone seeking employment at Airwallex is considered based on merit, qualifications, competence and talent. We don't regard color, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status when making our hiring decisions. If you have a disability or special need that requires accommodation, please let us know. #BI-Hybrid

Apollo.io is the leading go-to-market solution for revenue teams, trusted by over 500,000 companies and millions of users globally, from rapidly growing startups to some of the world's largest enterprises. Founded in 2015, the company is one of the fastest growing companies in SaaS, raising approximately $250 million to date and valued at $1.6 billion. Apollo.io provides sales and marketing teams with easy access to verified contact data for over 210 million B2B contacts and 35 million companies worldwide, along with tools to engage and convert these contacts in one unified platform. By helping revenue professionals find the most accurate contact information and automating the outreach process, Apollo.io turns prospects into customers. Apollo raised a series D in 2023 and is backed by top-tier investors, including Sequoia Capital, Bain Capital Ventures, and more, and counts the former President and COO of Hubspot, JD Sherman, among its board members. Your Role & MissionAs a Senior AI Engineer on our AI Engineering team, you will be responsible for building and productionizing advanced AI systems powered by Large Language Models (LLMs) and intelligent agents. You'll work on critical Apollo capabilities including our AI Assistant, Autonomous AI Agents, Deep Research Agents, Conversational Assistant, Semantic Search, Search Personalization, and AI Power Automation features that directly impact millions of users' productivity. The mission of our AI teams is to leverage Apollo's massive scale data and cutting-edge AI to understand and predict user behaviors, personalize experiences, and optimize every stage of the customer journey through intelligent automation. What You'll Be Working OnAI Assistant & Agent Systems - Agent Architecture & Implementation: Build sophisticated multi-agent systems that can reason, plan, and execute complex sales workflows - Context Management: Develop systems that maintain conversational context across complex multi-turn interactions - LLM and Agentic Platforms: Build scalable large language model and agentic platforms that enable widespread adoption and viability of agent development within the Apollo ecosystem - Backend Systems: Build back-end systems necessary to support the agents. - AI features: Conversational AI, Natural Language Search, Personalized Email Generation and similar AI features Classical AI/ML (Optional Focus) - Search Scoring & Ranking: Develop and improve recommendation systems and search relevance algorithms - Entity Extraction: Build models for automatic company keywords, people keywords, and industry classification - Lookalike & Recommendation Systems: Create intelligent matching and suggestion engines Key Responsibilities - Design and Deploy Production LLM Systems: Build scalable, reliable AI systems that serve millions of users with high availability and performance requirements - Agent Development: Create sophisticated AI agents that can chain multiple LLM calls, integrate with external APIs, and maintain state across complex workflows - Prompt Engineering Excellence: Develop and optimize prompting strategies, understand trade-offs between prompt engineering vs fine-tuning, and implement advanced prompting techniques - System Integration: Build robust APIs and integrate AI capabilities with existing Apollo infrastructure and external services - Evaluation & Quality Assurance: Implement comprehensive evaluation frameworks, A/B testing, and monitoring systems to ensure AI systems meet accuracy, safety, and reliability standards - Performance Optimization: Optimize for cost, latency, and scalability across different LLM providers and deployment scenarios - Cross-functional Collaboration: Work closely with product teams, backend engineers, and stakeholders to translate business requirements into technical AI solutions Required QualificationsCore AI/LLM Experience (Must-Have) - 7+ years of software engineering experience with a focus on production systems - 1.5+ years of hands-on LLM experience (2023-present) building real applications with GPT, Claude, Llama, or other modern LLMs - Production LLM Applications: Demonstrated experience building customer-facing, scalable LLM-powered products with real user usage (not just POCs or internal tools) - Agent Development: Experience building multi-step AI agents, LLM chaining, and complex workflow automation - Prompt Engineering Expertise: Deep understanding of prompting strategies, few-shot learning, chain-of-thought reasoning, and prompt optimization techniques Technical Engineering Skills - Python Proficiency: Expert-level Python skills for production AI systems - Backend Engineering: Strong experience building scalable backend systems, APIs, and distributed architectures - LangChain or Similar Frameworks: Experience with LangChain, LlamaIndex, or other LLM application frameworks - API Integration: Proven ability to integrate multiple APIs and services to create advanced AI capabilities - Production Deployment: Experience deploying and managing AI models in cloud environments (AWS, GCP, Azure) Quality & Evaluation Focus - Testing & Evaluation: Experience implementing rigorous evaluation frameworks for LLM systems including accuracy, safety, and performance metrics - A/B Testing: Understanding of experimental design for AI system optimization - Monitoring & Reliability: Experience with production monitoring, alerting, and debugging complex AI systems - Data Pipeline Management: Experience building and maintaining scalable data pipelines that power AI systems What Makes a Great CandidateProduction-First Mindset - You've built AI systems that real users depend on, not just demos or research projects - You understand the difference between a working prototype and a production-ready system - You have experience with user feedback, iterative improvements, and feedback systems Technical Depth with Business Impact - You can design end-to-end systems, including back-end systems, asynchronous workflows, LLMs, and agentic systems - You understand the cost-benefit trade-offs of different AI approaches - You've made decisions about when to use different LLM providers, fine-tuning vs prompting, and architecture choices Evaluation & Quality Excellence - You implement repeatable, quantifiable evaluation methodologies - You track performance across iterations and can explain what makes systems successful - You prioritize safety, reliability, and user experience alongside capability Adaptability & Learning - You stay current with the rapidly evolving LLM landscape - You can quickly adapt to new models, frameworks, and techniques - You're comfortable working in ambiguous problem spaces and breaking down complex challenges Our AI Impact at ApolloJoin a team that's already making significant impact: - Our AI Assistant helps sales teams automate research, scoring, and outreach processes - Assisted Prompting Mode allows users to leverage AI power-ups without being prompt engineering experts - Our AI email assistant processes hundreds of thousands of words monthly for Professional plan user - We help users "book more meetings in less time by automating research, scoring, outreach, & more with embedded AI sales assistants" If you're looking for a place where your AI engineering work directly impacts millions of users, where you can push the boundaries of what's possible with LLMs and agents, and where your career can thrive in the AI-native future—Apollo is the place for you. Application InstructionsTo help us identify candidates with strong real-world AI engineering experience, please answer the following five short screening questions directly in your application (2–5 sentences per response). Applications without answers to these questions will not be reviewed. Apollo.io Tech Blog : deep dives into engineering, product design, and company-culture stories from the Apollo team, offering behind-the-scenes insight into how Apollo builds and scales its B2B sales platform We are AI NativeApollo.io is an AI-native company built on a culture of continuous improvement. We’re on the front lines of driving productivity for our customers—and we expect the same mindset from our team. If you're energized by finding smarter, faster ways to get things done using AI and automation, you'll thrive here. Why You’ll Love Working at ApolloAt Apollo, we’re driven by a shared mission: to help our customers unlock their full revenue potential. That’s why we take extreme ownership of our work, move with focus and urgency, and learn voraciously to stay ahead. We invest deeply in your growth, ensuring you have the resources, support, and autonomy to own your role and make a real impact. Collaboration is at our core—we’re all for one, meaning you’ll have a team across departments ready to help you succeed. We encourage bold ideas and courageous action, giving you the freedom to experiment, take smart risks, and drive big wins. If you’re looking for a place where your work matters, where you can push boundaries, and where your career can thrive—Apollo is the place for you. Learn more here!

• Lead the design and implementation of AI architectures, frameworks, and reusable patterns that support scalable, production-ready AI systems. • Serve as the technical authority for AI initiatives, helping teams make sound decisions around model selection, infrastructure, security, and performance. • Design, build, and maintain AI-powered services and applications using Python and modern AI/LLM tooling. • Integrate and operationalize large language models and AI services, including Anthropic, within real-world production environments. • Architect and deploy AI workloads on AWS, including model hosting, inference pipelines, monitoring, and cost optimization. • Collaborate with product, engineering, and client stakeholders to translate business problems into effective AI solutions. • Establish best practices for AI development, including prompt design, evaluation, testing, observability, and responsible AI usage. • Mentor and guide engineers working with AI technologies, raising the overall AI maturity of the organization. • Stay current with emerging AI tools, frameworks, and industry trends, and proactively recommend improvements and innovations.

At Wasabi, we’re a proven collection of pioneers, visionaries and disruptive doers. We see things differently than our competitors, and we make our mark in the industry by challenging the norm and delivering the unexpected and improbable. We’re a fast-growing company taking the Cloud Storage industry by storm and recognized as one of the best places to work in Boston. Wasabi hot cloud storage is a new class and category of cloud storage, breaking all traditional barriers and boundaries of storage with a disruptive value proposition of being 1/5th the cost of AWS S3, faster than the competition, with no fees for egress or API requests. Cloud storage has never been so simple, so fast and so inexpensive. It’s all part of our vision to make cloud storage the next great global utility, just like electricity. Sr. Enterprise AI Engineer United States of America At Wasabi, we’re a proven collection of pioneers, visionaries and disruptive doers. We see things differently than our competitors, and we make our mark in the industry by challenging the norm and delivering the unexpected and improbable. We’re a fast-growing company taking the Cloud Storage industry by storm and recognized as one of the best places to work in Boston. Wasabi hot cloud storage is a new class and category of cloud storage, breaking all traditional barriers and boundaries of storage with a disruptive value proposition of being dramatically lower cost than legacy hyperscalers, faster than the competition, with no fees for egress or API requests. Cloud storage has never been so simple, so fast and so inexpensive. It’s all part of our vision to make cloud storage the next great global utility, just like electricity. Role Description: Enterprise AI Engineer . *Principals only. No recruiters. Role Purpose: Wasabi is seeking an AI Engineer to help build and scale our Enterprise AI Platform. This platform will be the foundation that enables AI assistants, agents, and AI-powered applications across Wasabi’s business functions. In this role, you’ll be a hands-on engineer who can translate business needs into concrete AI solution designs, implement core platform and application components, and drive solutions into production with measurable impact. You’ll operate at the intersection of AI innovation, software engineering, and business operations. You will partner closely with stakeholders across Sales, Marketing, Finance, HR, Legal, Customer Support, and IT to deliver secure, reliable, and scalable AI capabilities that elevate productivity and decision-making across the company. Responsibilities: - - Design and implement AI-powered solutions (assistants, agents, and apps) that solve business problems across enterprise functions. - Build platform capabilities for modern AI workloads, including retrieval-augmented generation (RAG), agent orchestration, evaluation, and production inference services. - Implement scalable services that support low-latency, high-throughput AI applications, while meeting reliability, security, and cost objectives. - Develop reusable patterns, libraries, and best practices that enable teams to safely and efficiently build on the Enterprise AI Platform. - Support rapid experimentation (POCs), evaluate emerging AI tools/frameworks, and help evolve platform architecture to incorporate successful innovations into production. - Contribute to MLOps pipelines (training, fine-tuning, versioning, deployment, monitoring, drift detection) to streamline the model lifecycle. - Help define and implement automated testing strategies for AI solutions (quality, safety, regression, hallucination checks, latency, and robustness). - Partner with Data/Analytics, Security, IT, and Engineering teams to ensure strong data governance, privacy protections, and responsible AI practices. - Contribute to team engineering excellence through code reviews, documentation, and knowledge-sharing. Requirements: - - 5+ years of experience in software engineering or applied AI/ML engineering, with experience building production services. - Demonstrated ability to design and deliver AI/ML-powered applications and/or platform capabilities in real-world environments. - Solid understanding of core AI concepts and modern Generative AI patterns (RAG, prompt engineering, evaluation, agentic workflows). - Experience with the AI lifecycle: data pipelines, training/fine-tuning (where applicable), evaluation, deployment, and monitoring. - Proficiency in one or more of: Python, Go, Java, or similar languages with strong fundamentals in APIs, reliability, observability, and performance. - Experience with modern AI/ML frameworks (e.g., PyTorch, TensorFlow, JAX) and cloud AI/ML platforms (AWS, GCP, Azure). - Strong communication skills and the ability to work effectively with technical and non-technical stakeholders. Nice to have: - - BS in CS/ML or related field, or equivalent practical experience. - Experience with security and privacy controls for AI systems (PII handling, access control, guardrails, auditability). - Experience working with distributed systems and large-scale data platforms. Base Salary – $160,000 - $200,000 The base salary range reflects the full range for this position at Wasabi Technologies. At Wasabi, we believe in paying fairly and competitively, and individual compensation is determined based on factors such as job-related experience, skills, location, and internal equity. Base pay is just one part of our total rewards approach. Depending on role eligibility, Wasabi team members may also receive additional compensation and benefits, including bonus or variable compensation, equity, and a comprehensive benefits package designed to support both professional growth and personal well-being. Wasabi Technologies is an Equal Opportunity Employer. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.