Fictiv Exists to Enable Hardware Innovators to Build Better Products, Faster Fictiv exists
to help product innovators create. Fictiv is a global manufacturing and supply chain company that enables organizations to scale globally across Fictiv’s four global manufacturing centers in India, Mexico, China, and the U.S.. Companies use Fictiv to access high-quality production, optimize supply chain logistics, and mitigate supply chain risk—ensuring they can move from prototype to full-scale manufacturing with speed and confidence. To date, Fictiv has delivered more than 35 million commercial and prototype parts for industries such as aerospace, robotics, automotive, climate tech, and more, helping them innovate faster, free up precious resources, and drive profitable growth. Impact In This Role As our Principal Product Manager - AI & Intelligent Manufacturing Systems, you’ll serve as a strategic and technical thought leader driving the vision, roadmap, and execution of AI-powered capabilities across Fictiv’s Manufacturing Quoting and Fulfillment Platform. This is a highly visible, high-leverage role — one that shapes how AI and automation become foundational to Fictiv’s operating system for new product development (NPD). You’ll partner directly with our AI R&D, data science, and platform architecture teams to define the core intelligence layer that powers quoting, supply orchestration, and manufacturing decision-making at scale. You will own and evolve the product strategy that fuses advanced AI models, data-driven automation, and manufacturing domain intelligence into a cohesive system that sets new standards for operational efficiency, precision, and speed. This role is ideal for a seasoned product leader with experience bringing AI-first enterprise platforms to life — someone equally comfortable discussing model architectures and data pipelines as they are business value and market differentiation. You will report to the VP, Product Management. Areas of Responsibility: 1. AI Technology Strategy & Product Vision - Define the long-term AI technology strategy for Fictiv’s digital manufacturing platform — including where and how to leverage LLMs, machine learning, computer vision, and reinforcement learning - Partner with AI research and engineering leadership to translate R&D advances into scalable, customer-facing capabilities - Identify and prioritize core AI product opportunities — from intelligent quoting and auto-classification of 3D models to predictive supplier matching and adaptive routing engines - Drive the architectural vision for Fictiv’s AI intelligence layer, ensuring alignment between data infrastructure, ML systems, and platform integration - Evangelize the role of AI within the organization — educating teams on capabilities, limitations, and ethical deployment of intelligent systems 2. Deep Technical Product Leadership - Serve as the product owner for AI infrastructure and model lifecycle management, including data acquisition, training, deployment, monitoring, and feedback loops - Partner with ML engineers and data scientists to design human-in-the-loop workflows that continuously improve system accuracy and explainability - Own the AI feature pipeline: define use cases, establish model performance metrics (precision, recall, latency, cost), and measure impact on business KPIs (quote accuracy, margin, lead time) - Collaborate with platform engineering to ensure scalability, modularity, and compliance in AI integrations - Drive responsible AI practices, including fairness, transparency, and auditability in model-driven decision systems 3. Solutions Integration & Application Development - Lead the development of AI-driven application modules — such as automated quoting, manufacturability assessment, supplier recommendation, and production forecasting - Work with product teams across quoting, fulfillment, and partner management to identify where intelligence adds differentiated value - Ensure AI and automation capabilities are embedded seamlessly into Fictiv’s core user experiences and operational workflows - Act as a bridge between AI technology development and solution commercialization, ensuring innovations move efficiently from lab to production 4. Metrics, Experimentation, and Validation - Define the performance framework for all AI-enabled systems, including model metrics (accuracy, throughput, latency), business KPIs (margin improvement, cycle time reduction), and adoption metrics - Lead data-informed experimentation programs to validate new model capabilities and measure real-world impact before scaling - Champion continuous learning loops between R&D, product, and operations teams 5. Cross-Functional & Executive Influence - Partner with senior leadership across Product, Engineering, Data, and Operations to align AI investments with strategic business outcomes - Influence architecture, resource allocation, and data strategy decisions that affect Fictiv’s AI roadmap - Mentor and guide other product managers in the organization on AI-first thinking and technical product management best practices - Represent Fictiv externally — at conferences, customer forums, and AI ecosystem events — as a thought leader in intelligent manufacturing systems Experience/Qualifications: Required - 10+ years of product management experience, including 4+ years leading AI or ML-driven products from research to production - Proven track record building AI-first SaaS or enterprise systems, ideally in manufacturing, supply chain, logistics, or industrial automation - Deep understanding of AI technologies, including LLMs, supervised/unsupervised ML, computer vision, or predictive analytics pipelines - Demonstrated success collaborating with AI research teams and data engineering to operationalize models into scalable, production-grade systems - Fluency in data infrastructure concepts (feature stores, inference APIs, model retraining, observability) - Strong technical intuition and ability to engage deeply with engineers and data scientists on architecture, experimentation, and trade-offs. - Analytical rigor and comfort with experimentation frameworks, A/B testing, and quantitative product measurement - Exceptional communication and influence skills — able to connect technical complexity to business impact and inspire alignment across functions Preferred - Domain experience in manufacturing, supply chain, or CAD/CAM ecosystems - Experience designing or managing systems with human-in-the-loop AI, active learning, or automated decision-support models - Working knowledge of product data ontologies, graph databases, or knowledge modeling for industrial applications - Track record of thought leadership or published work on AI strategy, ML productization, or applied AI ethics Physical Demands The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee routinely is required to sit; walk; talk and hear; use hands to keyboard, fingers, handle, and feel; stoop, kneel, crouch, twist, crawl, reach, and stretch. Perks and Benefits - Competitive medical, dental, and vision insurance - 401K plan - Monthly Virtual Work stipend for things like food, internet, travel, pet care, health and wellness - Annual Education stipend - Parental leave programs - Paid volunteer days - Onboarding setup, including: standing desk, laptop, monitor, and chair, and a stipend for additional items such as headphones, blue light glasses, or any other ergonomic supplies you may want or need - And much, much more! Fictiv is continuing to expand our remote US workforce. Applicants from the following states are eligible to apply: Arizona (AZ), California (CA), District of Columbia, (DC), Delaware (DE), Florida (FL), Georgia (GA), Hawaii (HI), Iowa (IA), Illinois (IL), Indiana (IN), Kansas (KS), Massachusetts (MA), Maryland (MD), Michigan (MI), Minnesota (MN), Missouri (MO), North Carolina (NC), New Hampshire (NH), New Jersey (NJ), New York (NY), Nevada (NV), Ohio (OH), Oregon (OR), South Carolina (SC), Texas (TX), Tennessee (TN), Utah (UT), Virginia (VA), Washington (WA), West Virginia (WV), Wisconsin (WI), Wyoming (WY) Salary Range: $210,000 to $230,000 per year, based upon experience Interested in learning more? We look forward to hearing from you soon. About Fictiv Fictiv is transforming how the next rockets, self-driving cars, and life-saving robots are designed, developed, and delivered to customers around the world. People who succeed at Fictiv are talented, creative, and driven to achieve professional excellence and support our vision to help product innovators create. We’re actively seeking teammates who: - Bring diverse perspectives and experience to our culture and company. - Excel at being part of a strong, empathetic team. - Thrive in an environment emphasizing respect, honesty, collaboration, and growth. - Have an ‘always learning’ mindset that celebrates learning, not just wins. - Help us continue to build a world-class organization that values the contributions of all of our teammates We encourage applications from members of underrepresented groups, including but not limited to women, members of the LGBTQ community, people of color, people with disabilities, and veterans.

• Build and operate an AI-powered content production system • Own Curri’s SEO strategy end-to-end • Design and execute AI-powered outbound campaigns targeting key accounts • Build and manage paid acquisition channels • Own lifecycle and email marketing automation • Define and operationalize Curri’s brand voice • Lead product marketing efforts • Own and evolve Curri’s marketing technology stack • Build and deploy AI-driven workflows and automations • Establish performance dashboards • Lead and develop Curri’s existing marketing team • Partner closely with Sales, Revenue Operations, and Product

WHO WE ARE Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com. The Role The Zeta AI R&D team sits at the heart of our technology and delivers on Zeta Global’s core brand promise: state-of-the-art marketing technology innovation. What You Will Do Zeta Global’s technology platform supports a real-time bidding system handling over 100 billion events per day, a reporting system aggregating and analyzing terabytes of data in real time, and a learning system applying machine learning and AI techniques to more than 40 petabytes of data. Together, these systems ensure Zeta serves the right advertisement to the right user at the right time. At the core of this platform is our Artificial Intelligence and Machine Learning team, which builds the models and decision-making systems that power Zeta’s products. This role is focused on post-training and alignment of large language models, with an emphasis on Supervised Fine-Tuning (SFT), preference optimization, and production operation of agentic LLM systems. As a Lead AI Engineer, you will own the end-to-end post-training lifecycle of LLMs—from SFT data curation and training strategy through evaluation, deployment, monitoring, and iteration—using platforms such as OpenAI and AWS Bedrock. Specifically, you will: - Lead Supervised Fine-Tuning (SFT) of large language models in production, shaping instruction-following, reasoning quality, tone, and domain-specific behavior - Extend SFT pipelines with instruction tuning and preference-based optimization (e.g., RLHF-style approaches or direct preference optimization) - Design, curate, and maintain high-quality SFT and preference datasets, combining human-labeled and synthetic data tailored to real-world marketing and decisioning use cases - Own model evaluation and benchmarking, including: - Offline behavioral evals (instruction adherence, reasoning depth, hallucination rates) - Online experiments and A/B tests - Continuous regression detection and performance monitoring - Develop and operate agentic LLM systems, enabling multi-step reasoning, tool use, workflow orchestration, and decision execution - Implement and optimize prompting, retrieval-augmented generation (RAG), memory, and tool-calling strategies, with a clear understanding of when to solve problems via SFT versus prompting - Partner closely with data engineering, platform, and product teams to integrate fine-tuned models into high-throughput, low-latency systems - Establish best practices for LLM versioning, experimentation, deployment, rollback, governance, and safety - Provide technical leadership and mentorship to engineers working on applied AI and LLM systems Who You Are You are deeply interested in how LLM behavior changes through SFT and post-training, especially in real production environments. You enjoy improving models through data, evaluation, and iteration—not just prompt engineering. You take ownership of outcomes, from model quality and alignment to reliability, latency, and cost. Required Experience and Skills - Significant hands-on experience with Supervised Fine-Tuning (SFT) of LLMs in production, beyond prompt-only approaches - Direct experience using OpenAI APIs and/or AWS Bedrock for SFT, post-training, and deployment - Strong understanding of LLM post-training workflows, including data preparation, instruction tuning, evaluation methodologies, and common failure modes - Experience building and operating agentic LLM systems (tool use, multi-step reasoning, workflow orchestration) - Proficiency in Python and modern ML frameworks (e.g., PyTorch) - Experience operating ML systems in distributed, production environments - Strong intuition for trade-offs between model quality, latency, cost, safety, and scalability BENEFITS & PERKS - Unlimited PTO - Excellent medical, dental, and vision coverage - Employee Equity - Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!! SALARY RANGE The salary range for this role is $200,000 - $215,000, depending on location and experience. PEOPLE & CULTURE AT ZETA Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression. We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here: https://zetaglobal.com/blog/a-look-into-zetas-ergs/ ZETA IN THE NEWS! https://zetaglobal.com/press/?cat=press-releases #LI-YW1

Southern New Hampshire University is a team of innovators. World changers. Individuals who believe in progress with purpose. Since 1932, our people-centered strategy has defined us — and helped us grow a team that now serves over 180,000 learners worldwide. Our mission to transform lives is made possible by talented people who bring diverse industry experience, backgrounds and skills to the university. And today, we're ready to expand our reach. All we need is you. Make an impact — from near or far At SNHU, you'll have the option to work remotely in the following states: Alabama, Arizona, Arkansas, Delaware, Florida, Georgia, Hawaii, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Mississippi, Missouri, Nebraska, New Hampshire, New Mexico, North Carolina, North Dakota, Ohio, Oklahoma, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, West Virginia, Wisconsin and Wyoming. We ask that our remote employees have access to a reliable internet connection and a dedicated, properly equipped workspace that is free of distractions. Employees must reside in, and work from, one of the above approved states. The opportunity Southern New Hampshire University (SNHU) is looking for an experienced Senior Python Backend Engineer. You will report directly to the Vice President of AI Engineering and you will engineer the backend systems that power our agentic AI learning platform, empowering human-centered learning for the age of AI. As a backend and platform engineer with data engineering skills, you'll build the infrastructure that powers our AI learning platform. You'll also ensure our Data Science team has the systems they need to measure the effectiveness and guide personalization. You will work remotely from any of our approved States #LI-Remote What you'll do: - Agentic backend and data platform** - You will design and implement scalable APIs for agent orchestration and learner interaction - You will build data pipelines that feed agent evaluation and continuous improvement cycles - You will create event streaming infrastructure for real-time learner interaction analysis - You will ensure data quality and accessibility for training and evaluating learning agents - You will improve data infrastructure for cost and performance in close coordination with Data and ML teams - This is a remote position Measurement and evaluation - Design and implement rigorous evaluation frameworks to measure agent performance and improve cycles - Develop LLM evaluation processes and perform error analysis to identify systemic improvements for agentic learning systems - Support instrumentation that makes evaluation relevant (metrics, traces/logs, and analysis workflows) On-call and incident response - Participate in on-call rotation and incident response for learning platform reliability - Contribute to runbooks, postmortems, and reliability improvements as we evolve our operating model What we're looking for: - 5+ years production Python experience at scale - AWS expertise (Lambda, DynamoDB, S3, Glue, and Athena) - Experience with a relational database such as MySQL, PostgreSQL, or Oracle - Experience with agentic AI architectures and evaluation frameworks - Data pipeline development (streaming and batch) - Infrastructure as Code experience (CDK, Terraform) - Production SaaS experience, including participation in on-call / incident response - Experience in GitHub Actions or similar CI/CD platforms - Experience communicating updates and resolutions to customers and other partners) AI-Augmented Development: - Active user of AI development tools (GitHub Copilot, Cursor, Claude Code, Codex) with personal projects and evolution over the past 12 months - Demonstrated examples of AI-augmented productivity gains - Enthusiasm for pushing boundaries of AI-assisted engineering We believe real innovation comes from inclusion - where different experiences, perspectives and talents are celebrated. So if you're wondering whether SNHU is right for you, take the leap and apply. You might be just the person we're looking for. Compensation The annual pay range for this position is $113,908.00 - $182,287.00. Actual offer will be based on skills, qualifications, experience and internal equity, in addition to relevant business considerations. We expect this position to be hired in the following target hiring range $125,868.00 - $170,293.00. Exceptional benefits (because you’re exceptional) You’re the whole package. Your benefits should be, too. As a full-time employee at SNHU, you’ll get: - High-quality, low-deductible medical insurance - Low to no-cost dental and vision plans - 5 weeks of paid time off (plus almost a dozen paid holidays) - Employer-funded retirement - Free tuition program - Parental leave - Mental health and wellbeing resources