Partner Development Manager Jobs

Lead Systems Integrator Company: The Boeing Company Boeing Defense, Space & Security (BDS) is seeking a Lead Systems Integrator (Level 4) to support an Air Dominance Fixed Wing Proprietary Program in St. Louis, MO . Step into a fast-paced, cutting-edge program where your expertise will drive the design, integration, and testing of advanced, cloud-based systems that empower mission planning, debrief, and tactical Command & Control (C2) solutions for fixed-wing platforms. In this role, you will lead the development, analysis, and integration of innovative engineering solutions for critical Ground System capabilities and ensure seamless support for ground systems from initial design through to final delivery. You will partner closely with the team’s test lead as well as the overall chief integrator who oversees all activities related to design, integration, and test. You will work with a high-performing, cross-functional team in an agile environment, driving next-generation capabilities from design through delivery. This role offers the chance to innovate with open-architecture, model-based designs and collaborate across disciplines to support critical defense missions. You champion best practices, processes, and standards for the integration team, mentor systems and electrical engineers, and coach solution leads on execution. If you’re passionate about advancing mission-critical systems and thrive in a collaborative, fast-moving environment, this is your opportunity to make a significant impact. Position Responsibilities Lead team of systems and electrical engineers in behavior modeling and requirements decomposition for system, sub-system, and software design

We are seeking an experienced Paid Media Audience Strategy & Data Architecture Lead to drive audience planning, activation strategy, and data-enabled marketing initiatives across the paid media ecosystem. This role combines strategic audience development with data architecture expertise, helping the organization identify, prioritize, and activate audiences that drive business outcomes. The successful candidate will lead the development of audience frameworks that answer key strategic questions: Who should we target? When should we engage them? Where should we reach them? Why are they valuable? Working closely with Marketing, Analytics, Data Science, Media, and Technology teams, this individual will translate customer insights and business goals into scalable audience strategies while ensuring data is appropriately integrated, governed, and activated across MarTech and AdTech platforms. The ideal candidate is a strategic audience expert who understands how to combine customer insights, first-party data, and marketing technology to develop effective targeting strategies. They can define who to target, when to engage them, where to activate them, and why they matter, while partnering across teams to operationalize those strategies and drive measurable business outcomes. Responsibilities: Audience Strategy & Planning: Develop audience strategies that support customer acquisition, cross-sell, engagement, and retention objectives, define target audience frameworks using customer behavior, lifecycle stage, demographics, transactional data, and behavioral signals, determine the optimal timing, channel, and messaging approach for audience engagement, partner with business stakeholders to identify high-value audience opportunities aligned with strategic priorities and establish audience selection methodologies, segmentation standards, and measurement frameworks. Customer Insights & Audi

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. The HBM Design Technology Package Co-Optimization (DTPCO) organization is seeking a Staff Engineer! Lead the design and development of test vehicles that enable technology learning and risk reduction for future HBM products! This role serves as a key technical contributor within DTPCO, partnering closely with Architecture, Design, Layout, Product Engineering, Reliability, and Advanced Packaging teams to translate emerging product requirements and technology challenges into actionable test vehicle solutions. You will apply expertise in semiconductor design, physical implementation, silicon characterization, and advanced packaging technologies to define test structures, develop validation strategies, and generate data that drives product decisions across future HBM generations. Unlike a traditional product role centered on ownership of product blocks, this position emphasizes enabling learning in development and engineering. It does so by developing representative test vehicles and characterization structures. Key Responsibilities Serve as a technical lead for HBM test vehicle design and structure development within DTPCO. Partner with HBM product, technology and reliability team. Define and implement test structures targeting key learning areas such as package interaction and reliability Drive test vehicle content definition, structure specifications, measurement requirements, and validation objectives. Analyze silicon characterization and qualification results to identify optimization opportunit

Work Flexibility: Remote As a Senior Lead, Data Engineering, you will serve as a technical leader who helps shape the future of enterprise data solutions. In this role, you will drive complex data initiatives, influence technical strategy, and partner with teams across the organization to build scalable, high-impact data products. This is an opportunity to solve challenging business problems while mentoring fellow engineers and elevating data engineering best practices. What You Will Do Lead the architecture, development, and modernization of scalable enterprise data platforms that support global procurement analytics and business transformation. Define and help execute a multi-year data engineering strategy focused on platform scalability, reliability, automation, technical debt reduction, and long-term maintainability. Design, build, and optimize Azure-based data solutions using technologies such as Databricks, Delta Lake, Azure Data Factory, Azure DevOps, CI/CD pipelines, and infrastructure automation. Integrate and harmonize data across multiple ERP systems by standardizing supplier, purchasing, and master data into common enterprise data models. Partner with procurement analysts, architects, engineers, and business stakeholders to translate complex business needs into reusable, scalable data products and engineering solutions. Establish engineering standards, conduct architecture reviews, improve documentation, and mentor engineers to raise the overall technical capability of the team. Identify and implement AI-enabled approaches that accelerate development, improve data quality, automate documentation, support testing, and enhance analyst productivity. Evaluate and recommend tools, frameworks, patterns, and platform investments that improve performance, reliability, security, governance, and operational ef

The Data Analyst, Revenue Operations is responsible for turning data from multiple source systems into the reporting, models, and visualizations that power revenue, sales, and operations decision-making. Reporting into the Revenue Operations organization, this role combines hands-on SQL and data modeling with predictive segmentation, opportunity analysis, and dashboard development — and serves as a trusted reporting partner to teams across the business. You will work primarily within Revenue Operations while collaborating cross-functionally with Sales, Business and Technical Operations, Sales Enablement, Support, and Finance to get things done. About NMI NMI, a global leader in payment technologies, allows software and sales professionals to deliver payment innovations to their clients without having to build payment expertise in house. NMI enables our partners with choice, and challenges the one-size-fits-all approach to payments. You've probably used NMI in the last 24 hours without even realizing it. We're the platform that powers success for innovative tech created by SMBs, entrepreneurs and fintech startups. We're creative problem solvers who help visionaries smash through boundaries and think beyond what's possible so they can think about what's next. But we're not just built for the tech savvy. We democratize the latest payments technology so that everyone can realize the benefits of easy payments across the full spectrum of commerce. Our mission is to use our expertise to enable more payments, in more ways and more places. We provide ISOs, Fintech Innovators and Technologists the freedom to focus on what they do best, liberating them from restricted payment solutions and giving them access to the latest payment technology now and in the future. How We Work - Our Core Values * Be a Good Person, It's Simple. We treat everyone fairly and with respect. We lead with kindness, humility and integrity. We take the time to understand each other and our customers. And

AI/ML – Investment Services A Career with Point72's AI/ML – Investment Services Team The AI/ML – Investment Services team at Point72 spearheads the development of cutting-edge AI solutions that seek to transform our business processes and enhance enterprise intelligence. The team aims to bridge the gap between business challenges and technological innovation, collaborating with stakeholders across the firm and leveraging expertise in generative AI, data engineering, and machine learning. WHAT YOU'LL DO Build and scale core backend services and platforms that power generative AI applications and data infrastructure used across the firm’s investment workflows Design and implement high-throughput, low-latency data pipelines to ingest, normalize, and serve both structured and unstructured data Develop robust APIs and microservices to support model inference, feature serving, and downstream applications Integrate generative AI tools and model-serving workflows into production, including embedding stores, retrieval components, and fine-tuning pipelines Optimize system performance, cost, and reliability through profiling, capacity planning, and architectural improvements Implement automated testing, continuous delivery pipelines, monitoring, and incident response practices to maintain production health Partner with data scientists, AI engineers, product owners, and operations to translate models and prototypes into scalable, production-grade solutions Mentor engineers, lead code reviews, and establish engineering best practices for maintainability, security, and observability Own end-to-end delivery, operational runbooks, and metrics-driven measurement of feature impact and system reliability WHAT'S REQUIRED Bachelor’s degree in computer science, software engineering, or a related technical field Minimum 5+ years of professional experience building backend systems and production services Demonstrated experience designing and operating large-scale data engineering pipelines

A Career with Point72's Technology Team As Point72 reimagines the future of investing, our Technology group is constantly improving our company’s IT infrastructure, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts experimenting, discovering new ways to harness the power of open source solutions, and embracing enterprise agile methodology. We encourage professional development to ensure you bring innovative ideas to our products while satisfying your own intellectual curiosity. What you'll do Lead the design, development, and operation of scalable, enterprise-grade AI/ML architectures and systems with a strong emphasis on reliability, availability, and performance. Lead and mentor a team of engineers, driving technical direction, code quality, and iterative delivery of large-scale solutions. Partner closely with data scientists, engineers, product teams, and compliance to integrate AI/ML solutions into existing and new products. Own the end-to-end lifecycle of GenAI services, including LLM inference, model serving, and proxy/gateway layers that support multiple downstream applications. Define and uphold engineering best practices around observability, scalability, security, and cost efficiency for AI/ML platforms. Evaluate tools, technologies, and processes to ensure the highest quality and performance of AI/ML systems. Stay abreast of the latest advancements in AI/ML technologies and methodologies, and translate them into pragmatic solutions for the business. Ensure compliance with industry standards and best practices in AI/ML. What's required Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 10+ years of experience in software/AI/ML engineering, with a proven track record of successful delivery of complex, production-grade systems. Demonstrated experience building large-scale enterprise-grade services with high reliability, availability, and observability (SLO/SLA-driven en

We're looking for a Head of Enterprise & Field Marketing to lead and scale our global field marketing organization, own account-based marketing for our largest and most strategic accounts, drive alliances and partner marketing in service of enterprise growth and regional strength; and oversee our strategic events strategy and programs. This is a senior leadership role responsible for the strategy, team, and execution to drive high-quality pipeline and conversion for Diligent’s AI-powered GRC platform in all regions, and design programs that turns enterprise pipeline into revenue through a full-funnel approach, including integrated regional campaigns; 1:1/1:few ABM for named global accounts; bespoke strategic events that offer cut-through experiences for prospects and customers; and leveraging co-marketing of alliances and partnerships for net-new pipeline and brand expansion. You would be joining Diligent at an exciting moment in the company’s history, as they unleash their new AI-powered GRC platform to help General Counsels, Chief Compliance Officers, Audit and Risk Leaders. This is the result of nearly three years of intense development of agentic workflows inside the Diligent platform, as well as MCP/plug-in access to Diligent offerings - providing a robust, differentiated experience for clients who need solutions that accelerate and action critical business objectives, not just static reporting. Working closely with Sales and the broader GTM organization, you will lead an established, multi-region field marketing team and be responsible for evolving it from regional execution into a more specialized, account-centric growth engine — tightly aligned with enterprise sales leadership, customer success, global events, and partner teams. You'll own the budget, the roadmap, and the relationship with sales as the primary marketing partner for our highest-value opportunities. You w

At Scale, we develop reliable AI systems for the world’s most important decisions. Scale’s product marketing team is responsible for developing and executing strategies that drive awareness and engagement for Scale’s offerings amongst our core audiences. We take a data-driven approach to understand our customers’ needs and challenges, ensuring that their voices are reflected in product development and messaging. We partner closely with product, engineering, research, sales, comms, and the broader marketing team to create a cohesive customer experience across all our channels. We aim to provide valuable insights and resources that help our customers execute on their AI transformation journey. This role will focus on developing and optimizing vertical-specific messaging and content for Scale’s applications business to ensure our messaging resonates with core buyers across verticals. The ideal candidate combines strategic thinking with hands-on execution. You will: Develop clear, compelling messaging for enterprise offerings tailored to key personas within target verticals Create marketing assets, including slide decks, videos, blog posts, and one-pagers, that effectively communicate our value propositions to vertical leaders and support our sales team’s pursuits Lead positioning and sales enablement efforts to drive awareness and engagement for Scale’s offerings. Drive cross-functional marketing programs around target verticals, in conjunction with product, engineering, sales, and growth marketing to create a cohesive customer experience and contribute to pipeline targets Collaborate with field marketing and events teams to develop vertical-specific event strategies, content, and experiences that drive engagement within customer and target accounts Drive customer marketing efforts, creating both strategy and tactics to maximize the value Scale and customers get from our shared success, including case studies, testimonials, visual assets and event particip

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities. In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models. You will: Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities. Design and experiment new approaches to preference optimization. Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning. Excellent written and verbal communication skills Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals Previous experience in a customer facing role. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined du

Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities. In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models. You will: Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents. You’ll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA. Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities. Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning, and with LLM evaluation or benchmark development. Excellent written and verbal communication skills. Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals. Previous experience in a customer facing r

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Senior Staff Frontier Agents Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineering & Optimization Create sophisticate

Role Overview We are seeking a Staff Simulation Engineer to build an end-to-end aerial autonomy simulation stack at DoorDash Labs. This is a highly technical, hands-on leadership role focused on defining and implementing the simulation architecture that underpins autonomy development, validation, CI/CD testing, and pilot training. You will operate as the technical authority for simulation: owning core architecture decisions, developing key components yourself, and setting engineering standards. You will build and mentor a small, high-caliber simulation team while remaining deeply involved in implementation and system design. This role is ideal for someone who has built simulation systems from first principles, understands simulator internals deeply, and is excited to create a world-class platform from scratch. Key Responsibilities Architect and implement an end-to-end simulation stack for aerial autonomy at DoorDash Labs.. Develop high-fidelity simulation capabilities, including: Flight dynamics modeling Contact modeling and constraint handling Sensor and perception simulation Autonomy software-in-the-loop (SITL) integration Design and implement scalable simulation infrastructure to support: Regression testing in CI/CD pipelines Continuous validation of flight autonomy and autopilot software stack Mission-level testing and scenario generation Build cloud-deployed simulation systems to enable large-scale parallel testing and pilot training. Partner closely with autonomy, controls, and aircraft teams to ensure simulation fidelity and validation alignment. Establish technical direction, architecture standards, and performance benchmarks for simulation. Mentor and grow a small team of simulation engineers while remaining deeply hands-on. Required Qualifications Master’s or PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, Aerospace Engineering, or a related field. 10+ years of experience in robotics or physics-based simulation. Deep expe

About the Team DoorDash Labs, established in 2018, serves as the innovation hub for DoorDash, focusing on developing automation and robotics solutions to enhance last-mile logistics. The team's mission is to create technologies that support and augment human networks, aiming to improve efficiency for Dashers, merchants, and consumers alike. We’re ruthlessly focused on business impact. We are a highly senior team composed of former pioneers from a variety of different robotics industries. As of 2025, DoorDash has completed 10B lifetime deliveries. We’re focused on how to do the next 10B even better. About the Role We are seeking a highly motivated Senior Reliability & Test Engineer to join our team. This individual will play a key role in the development and validation of our unmanned platforms at the system and component levels. You will partner closely with EE, ME, and Autonomy teams to translate mission needs into robust, reliable hardware. The ideal candidate thrives in a fast-moving, cross-functional environment where reliability and test rigor determine program success. You will be hands-on in developing test methods and equipment to uncover failures before they happen in the field. You will partner closely with EE, ME, and Autonomy teams to translate mission needs into robust, reliable hardware. The ideal candidate thrives in a fast-moving, cross-functional environment where reliability and test rigor determine program success. You’re excited about this opportunity because you will… Architect and implement rigorous validation strategies, utilizing Python scripts for automation while leveraging CAD and shop tools to engineer bespoke test fixtures and hardware rigs. Oversee experimental execution across internal facilities and external laboratories, maintaining technical mastery over vibration tables, environmental chambers, DAQ systems, and ingress protection testing. Translate high-level vehicle reliability requirements into granula

MongoDB is seeking a highly motivated Senior Deal Strategy Analyst to join our Global Deal Strategy function. This role will act as a strategic partner to Sales leadership on complex, high-value deals and opportunities, bringing sound judgment and financial rigor to structuring that balances revenue, profitability, and market share priorities. This is a tremendous opportunity for an experienced deal strategy professional who thrives on ambiguity, enjoys influencing cross-functional stakeholders, and is relentless in their pursuit of excellence in a high-growth environment. We are looking to speak to candidates who are based in Singapore for our hybrid working model. Responsibilities Serve as a senior, trusted advisor to Sales leadership and cross-functional stakeholders on the structuring and execution of complex, non-standard, and high-value deals Independently evaluate and resolve non-standard deal requests, driving cross-functional solutions across Sales, Finance, and Legal with minimal oversight Review and approve key terms on quotes, ensuring accuracy and alignment with pricing, revenue recognition, and operational guidelines Ensure all transactions adhere to internal revenue recognition policies and operational guidelines, escalating and resolving edge cases as needed Lead the development and rollout of best practices and playbooks that increase sales efficiency and shorten cycle times across the global team Identify and implement opportunities to automate and streamline deal desk workflows using AI and automation tools (e.g., AI-assisted contract review, quote generation, deal analytics), reducing manual effort and turnaround time Drive deal reviews, early checkpoints, and enforcement of standard business practices and policies; identify and address systemic gaps in deal process Partner with Finance and Sales Operations leadership on forecasting, deal analytics, and continuous improvement of deal desk processes Present recommendations and deal strategy insigh