• Lead technical discovery and advisory engagements with customers to identify high-value AI use cases relevant to their industry and data • Advise on end-to-end AI deployment — model selection, training/fine-tuning strategies, inference optimization, data pipeline design, and evaluation/alignment/safety frameworks — optimized for Pure's platform • Collaborate cross-functionally to qualify and position AI opportunities, and develop proof-of-value prototypes that translate technical performance into business outcomes • Create AI enablement content for field teams, partners, and customers — technical walkthroughs, qualification guides, workshops, and vertical-specific use case frameworks • Present at industry conferences, publish technical content and peer-reviewed research, and represent Pure in engagements with strategic technology partners (NVIDIA, AMD, cloud providers, MSPs) • Operate autonomously in ambiguous environments — independently scoping high-impact initiatives and driving them to completion at the right pace

Our Mission and Opportunity Early education is one of the most important determinants of childhood outcomes, a critical support for working families, and a $175B market that remains underserved by modern technology. Brightwheel is the largest, fastest growing, and most loved platform in early ed, trusted by millions of educators and families every day. We are a three-time Cloud 100 company, backed by top investors including Addition, Bessemer, Emerson Collective, Lowercase Capital, Notable Capital, and Mark Cuban. Our Team Our team is passionate, talented, and customer-focused. We embody our Leadership Principles in our work and culture. We are a distributed team with remote employees across every US time zone, as well as select offices in the US and internationally. Who You Are You are an AI-native Director of Engineering who combines exceptional engineering judgment, product sense, and high standards with the ability to scale leaders, teams, and execution. You create clarity in ambiguous spaces, turn company priorities into high-velocity delivery, and lead by example in how modern engineering gets done. You care deeply about the CX your team ships, and you help make AI-native execution practical, repeatable, and fast across the organization. You will succeed in this role if you are: - Focused on business impact. You care about scaling brightwheel’s value and impact by orders of magnitude. You treat technology as a driver of growth and operational efficiency, always connecting engineering decisions to better outcomes for educators, administrators, and families. - A practitioner-leader. You do not lead from a distance. You use AI agents and modern tooling in your own work to raise the organization’s ambition, show what great looks like, and help teams adopt better ways of building. What You’ll Do brightwheel already supports the workflows that keep early education businesses running: enrollment, billing, staffing, classroom operations, family communication, and compliance. The next step is bigger. We can use AI to turn brightwheel from a system of record into a system of action, reducing toil, automating routine work, improving decision-making, and accelerating how we build. You will turn that opportunity into reality. You will build teams, systems, and AI-native ways of working that help brightwheel deliver more value to customers, move faster as an organization, and continuously raise the bar on product quality, reliability, and execution. In this role, you will: - Lead engineering teams that deliver AI-powered product and platform capabilities with clear impact. Reduce administrative toil, improve family responsiveness, streamline enrollment, and surface better insights for operators. - Build software that not only records information, but also recommends next steps, completes routine work, and automates meaningful parts of our customers’ day-to-day operations. - Use AI agents, automation, and modern tooling to improve how teams build, test, ship, and support software, increasing velocity and freeing up more capacity for high-value work. - Operate an AI hybrid engineering workforce in which engineers and agents work together effectively, with the tooling, guardrails, governance, evaluation, and observability required. - Apply the same AI-native mindset to internal functions like customer support and onboarding, helping the company become faster, more responsive, and more efficient as it scales. - Drive continuous improvements in quality, reliability, and security by using agentic workflows to catch issues earlier, reduce operational burden, and improve the product every week. - Hire and scale exceptional AI-native engineering talent, building a lean, high-performing organization with high standards, strong ownership, and a bias for action. - Make strong build-versus-buy, architecture, and platform decisions that balance short-term speed with long-term leverage and differentiation. What You’ve Done We are open to a variety of backgrounds, but qualified candidates usually bring: - A strong computer science foundation. You have a 4-year computer science degree or equivalent depth in core computer science topics, with the technical grounding to reason well across systems, abstractions, and tradeoffs. - A record of shipping battle-tested products at scale. You have helped deliver customer-facing software from pixels to metal, in either consumer or enterprise software. You have seen what it takes to make products succeed in real production environments with real customers and business stakes. - Applied AI experience in production. You have used AI, automation, or machine learning in high-stakes environments, whether in customer-facing products, internal systems, or engineering workflows. You understand what it takes to make these systems useful, reliable, safe, and cost-effective. - Experience leading through leaders. You have managed managers and senior engineers, building teams that consistently delivered meaningful product or platform outcomes in demanding, fast-paced environments. What Sets You Apart The candidates who will thrive in this role go beyond the standard management toolkit: - Product taste and judgment. You operate without needing a product manager crutch. You are excited by the challenge of defining the right thing to build, not just building it right. In the age of AI, you use your product intuition to bridge the gap between technical possibility and customer value. - High-stakes communication and influence. You are equally comfortable in the boardroom and the IDE. You can persuade a C-suite audience on high-stakes strategic bets while maintaining the deep technical respect of the engineers who are building the systems. - A proven talent magnet. You have a track record of building or turning around teams in highly competitive hiring arenas. You have successfully attracted and retained top talent. - You are a T-shaped leader, deeply expert in at least one domain but capable of becoming proficient just-in-time across science, data, security, infra, and UX. You use AI to multiply your learning speed, allowing you to handle the full breadth of a modern engineering organization. - Hands-on fluency with AI-native development. You do not just manage; you build. You have used AI assistants and agents to materially improve your own speed and quality, and you have a clear perspective on how to help an entire organization adopt these workflows effectively. Technology We work with: - AI & Automation: All the frontier models you expect, vector search, orchestration and agent frameworks, and modern AI coding tools like Claude Code / Cursor - Backend: Ruby on Rails, Sidekiq - Data: PostgreSQL on Amazon RDS, Redis, and event and analytics pipelines - Frontend: React with TypeScript and Emotion - Mobile: Native iOS (Swift) and Android (Kotlin with Jetpack Compose) - Cloud & Infrastructure: Docker, Kubernetes on Amazon EKS, GitHub Actions and FluxCD for CI/CD, and AWS services such as S3, CloudFront, CloudWatch, and SNS Brightwheel is committed to creating a diverse and inclusive work environment and is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, gender expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Protecting Our Applicants: Please be aware of recruiting scams impersonating Brightwheel. All legitimate communications come from @mybrightwheel.com addresses, and we never ask for payment or sensitive personal data as part of our hiring process. If you suspect fraudulent contact, reach out to security@mybrightwheel.com. Thank you for helping us keep our applicant community safe.

About Juniper Square Our mission is to unlock the full potential of private markets. Privately owned assets like commercial real estate, private equity, and venture capital make up half of our financial ecosystem yet remain inaccessible to most people. We are digitizing these markets, and as a result, bringing efficiency, transparency, and access to one of the most productive corners of our financial ecosystem. If you care about making the world a better place by making markets work better through technology – all while contributing as a member of a values-driven organization – we want to hear from you. Juniper Square offers employees a variety of ways to work, ranging from a fully remote experience to working full-time in one of our physical offices. We invest heavily in digital-first operations, allowing our teams to collaborate effectively across 27 U.S. states, 2 Canadian Provinces, India, Luxembourg, and England. We also have physical offices in San Francisco, New York City, Mumbai and Bangalore for employees who prefer to work in an office some or all of the time. About your role We're looking for an AI Engineer Intern to join our team who is excited to help transform the private markets. In this role, you’ll work alongside a talented and collaborative team focused on one of our top strategic initiatives - bringing cutting-edge AI innovation to a key product feature that will drive real change in the industry. As an intern, you’ll have a hands-on role in designing, building, and testing new AI-driven product features. This isn’t a side project - it's a core company priority with executive visibility and high impact. You’ll work in close partnership with engineers, product leaders, and mentors who are invested in your growth and success. You’ll also gain valuable exposure to company leadership, access to world-class mentorship, and the opportunity to contribute meaningfully to a product that’s reshaping how the private markets operate. For the right person, this internship can be a launchpad into a full-time role post-graduation. This opportunity is perfect for someone with a strong engineering foundation who is currently pursuing a master’s degree in AI or a related field - and who’s excited to innovate, learn fast, and make a real-world impact. This is a remote role based in the U.S. or Canada. The internship program runs for 11 weeks at 40 hours per week, with a scheduled start date of Monday, June 8th. There may be an opportunity to travel to our San Francisco office the final week to participate in the annual Hackathon. What you’ll do - Collaborate with engineers and product managers to design and prototype AI-powered features that directly impact a key product area at the core of our business - Contribute to the development, training, and evaluation of machine learning and natural language processing (NLP) models using industry-standard tools and frameworks - Work with large and complex datasets - performing data preprocessing, feature engineering, and analysis to support model development - Apply foundational machine learning and deep learning techniques to solve real-world problems in the private markets space - Assist with integrating AI models into production systems, including testing, validation, and iteration in collaboration with the engineering team - Support ongoing research and experimentation efforts, particularly around NLP and large language models (LLMs), to drive innovation in product development - Partner closely with engineering, design, and product stakeholders to evaluate the technical feasibility and ensure alignment of proposed AI features with the overall product vision and strategy. - Participate in regular team meetings, code reviews, and brainstorming sessions - bringing curiosity, ideas, and technical insight to the table - Receive mentorship from experienced AI and engineering leaders, while gaining exposure to company leadership and strategic initiatives - Contribute to documentation and knowledge sharing to help scale AI development efforts across the team - Take ownership of meaningful projects with the potential to influence long-term company strategy and product direction - Embrace a growth mindset - continuously learning new tools, methodologies, and concepts in the rapidly evolving field of AI Qualifications Education & Academic Background - Currently pursuing a Master’s degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, or a related quantitative field (e.g., Mathematics, Statistics, Physics) - Strong academic foundation with relevant coursework in algorithms, data structures, linear algebra, calculus, probability, and statistics - Completed or currently enrolled in courses in machine learning, deep learning, NLP, or computer vision (highly desirable) Technical Skills - Proficient in Python; experience with libraries such as TensorFlow, PyTorch, scikit-learn, NumPy, and Pandas is a plus - Familiarity with data manipulation, preprocessing, and feature engineering techniques - Exposure to databases (SQL/NoSQL) and data querying; experience with data visualization tools (e.g., Looker, Tableau, Power BI) is a bonus - Understanding of foundational ML algorithms (e.g., regression, decision trees, clustering) and the underlying mathematical concepts - A strong grasp of Large Language Model (LLM) mechanisms, including knowledge of sampling strategies, structured output generation, and function-calling capabilities. Hands-on experience with prompt engineering is a strong plus - Exposure to cloud platforms (e.g., AWS, GCP) and cloud-based ML services (e.g., Amazon SageMaker, Google AI Platform) is beneficial - Basic knowledge of software engineering practices, including version control (Git), Agile development, and API integration (REST, GraphQL) Soft Skills & Mindset - Strong analytical and problem-solving skills with a high attention to detail - Eagerness to learn and apply new AI concepts in a fast-paced, evolving environment - Clear and effective communication skills, both written and verbal - Collaborative mindset with the ability to contribute meaningfully to team discussions and technical problem-solving - Self-starter with curiosity, initiative, and a proactive approach to innovation Bonus Points - Personal AI/ML projects (e.g., GitHub portfolio) - Participation in AI/ML competitions or hackathons - Research experience or academic publications in AI-related areas - Contributions to open-source projects Compensation Compensation for this position includes an hourly rate. The U.S. hourly rate is $50.00 USD and the Canadian hourly rate is $57.00 CAD. #LI-BA1 #Juniper-US #Juniper-Canada #LI-Remote

About the role As an Applied AI Engineer at AlphaFMC, you will play a pivotal role in shaping how leading financial services organizations adopt and scale AI. You will work on high-visibility initiatives inside wealth management firms, banks, and insurance companies, where the stakes are high and the standards for performance, safety, and governance are non-negotiable. Your experience in data science, LLMs, and agentic AI will directly influence how our clients operate and compete. You will have real ownership across the full solution lifecycle, with visibility into both technical delivery and business outcomes, and meaningful input into the AI strategies we bring to market. What you'll do - Own the full lifecycle of AI/ML projects, including problem framing, data acquisition, feature engineering, model and LLM selection and fine-tuning, evaluation, deployment, monitoring, and continuous improvement. - Design, build, and maintain scalable data pipelines for ingestion, preprocessing, and feature engineering, supporting both structured and unstructured enterprise data. - Implement RAG pipelines using vector databases and embedding strategies to ground LLMs in proprietary enterprise data; fine-tune, prompt-engineer, and evaluate LLMs for domain-specific tasks; design and orchestrate agentic workflows including tool-using agents, multi-step planners, guardrails, and alignment mechanisms. - Establish robust evaluation frameworks covering hallucination checks, calibration, bias and fairness, and adversarial testing; build logging, telemetry, safeguards, governance artifacts, and documentation for model risk management. - Lead the end-to-end lifecycle of AI models from experimentation and prototyping to scalable deployment in production environments using MLOps best practices, CI/CD, and cloud platforms (AWS, Azure, GCP). - Optimize inference latency, throughput, and cost; establish monitoring and observability to ensure performance, safety, and reliability in mission-critical environments. - Work closely with AI engineers, software engineers, product managers, and business stakeholders to translate complex business problems into AI-native solutions with measurable impact. Qualifications - A bachelors' degree in a related field and at least 5 years of experience designing and deploying production-grade AI/ML solutions, including at least one production LLM agent or agentic workflow - At least 5 years' experience working in Python and SQL, with hands-on experience in AI/ML frameworks such as scikit-learn, TensorFlow, or PyTorch - Proven experience with cloud-native development and data warehousing solutions (Snowflake, Azure Data Lake, AWS S3, or equivalent) - Strong knowledge of LLMs, transformers, NLP, agentic modeling, and reinforcement learning concepts - Experience with open and commercial LLMs, RAG pipelines, and agent frameworks (LangGraph, LangChain Agents, DSPy, or equivalent) - Experience building data ETL/ELT pipelines and deploying models using Docker/Kubernetes, CI/CD, and monitoring/observability tools - Familiarity with model risk management and trustworthy AI practices, especially in regulated industries - Strong analytical, problem-solving, and communication skills; comfortable working across technical teams and business stakeholders How you know if you would be successful in this role - You demonstrate tenured experience across data science, LLMs, and agentic AI. You can move fluidly between model experimentation and production engineering, and you understand the tradeoffs between approaches. - You know how to establish and enforce evaluation frameworks to ensure production-ready deployment of AI/ML solutions, with particular sensitivity to the governance requirements of financial services and/or Insurance industries. - You work effectively with onshore and offshore engineers, product managers, and business stakeholders. - You can explain a RAG pipeline to a senior engineer and a hallucination risk to a compliance officer, adjusting your communication without dumbing things down. - You can employ modern AI/ML and GenAI design patterns to solve complex business problems and integrate advanced AI into application architectures with measurable impact. - You thrive in a fast-paced environment, stay current with a rapidly evolving AI landscape, and know when to adopt new tools and when to resist the hype. Other Info - Benefits Offered: Medical, Dental, and & Vision Insurance. Life, Short Term Disability, and Long Term Disability Insurance. 25 days of accrued PTO, paid holidays. Profit Sharing-based annual target bonus. Company sponsored 401(k) plan with match. Monthly wellness and tech stipend. - This role is not eligible for sponsorship at this time. - This position may require up to 15% travel (to client sites). - The position requires the employee to be able to work 8:30am - 5:30pm EST Monday through Friday. - The successful candidate will be subject to thorough background checks, including physical location verifications. - No agencies, please.