Top Product Engineer Jobs

The Lead AI Product Engineer will design, build, and operate AI agent systems, focusing on architecture, reliability, and performance while collaborating on user-centric workflows.

Coordinates electronic prototype and PCB new product introductions from design readiness through manufacturing and testing. Works with engineering, procurement, suppliers, and contract manufacturers to ensure materials, tooling, documentation, test strategies, and schedules are aligned. Supports DFM/DFA reviews, drives build issue resolution and root-cause analysis, maintains NPI documentation, manages supplier and manufacturing risks, and improves build quality and readiness. Travel to manufacturing locations may be required.

Performs electrical, physical, and statistical failure analysis for next-generation HBM semiconductor products. Identifies component failure mechanisms, fabrication and assembly defects, and test-flow marginalities using characterization techniques, AI tools, and statistical analysis. Coordinates improvement efforts with Product, Process, Quality, and Test Engineering teams to support reliability, production ramp, and mass production. The role requires a bachelor’s degree in a relevant engineering or science field and at least five years of related experience.

Investigates and resolves semiconductor product and process yield losses through root-cause analysis, physical failure analysis, statistical methods, data analytics, and AI-assisted workflows. Collaborates with R&D, manufacturing, marketing, and quality teams to improve product yield, performance, and reliability. Follows chemical safety and laboratory procedures while working rotating day and night shifts.

Designs, implements, and leads product security and resiliency across the full lifecycle for digitally-connected Boeing airplanes. Responsibilities include cloud security and PKI architecture, supplier security requirements, certification and compliance (RMF/DFARS/NIST 800-171), risk assessment, vulnerability management, DevSecOps/IaC support, regulatory coordination, research, and advising customers and stakeholders.

Leads a team supporting product integration, configuration management, engineering data management, baseline control, change management, and delivery for Boeing’s P-8 military aircraft program. Collaborates with engineering, program leadership, suppliers, customers, and cross-functional teams; ensures compliance with government standards; manages product data tools and presents to executive leadership. This is a 100% onsite role in Tukwila, Washington.

Leads product security engineering for satellite and ground systems, including cybersecurity architecture, RMF implementation, risk and vulnerability assessments, cryptographic keying, security requirements, certification, supplier security, and lifecycle resiliency. Coordinates with engineering teams, customers, government agencies, suppliers, and senior leadership while supporting classified environments and accreditation activities.

Design, integrate, and validate power distribution and power electronics hardware for autonomous mobile robot platforms. Responsibilities include PCB development from schematic capture through bring-up, power-budget and load analysis, component derating, component selection, troubleshooting power and thermal issues, and documenting architectures, test plans, and validation results. The engineer collaborates across hardware, wiring, software, and systems teams.

Secure CrowdStrike’s software supply chain and code-hosting environments by assessing GitHub organizations, open-source integrations, repositories, dependencies, and third-party packages. Implement repository guardrails, secret scanning, access controls, and automation; investigate supply-chain threats such as typosquatting and dependency confusion; promote secure coding and open-source compliance; and collaborate with engineering teams on security initiatives.

As a Product Engineer at Marble, you will build full-stack applications to enhance youth mental health access, collaborate on product features, and elevate engineering standards.

Lead cross-functional product engineering for SoC/CPU/GPU manufacturability from pre-silicon readiness through post-silicon bring-up. Own manufacturing flow, ATE/SLT test and correlation, yield improvement, silicon/package reliability qualification, PVTF characterization, and failure analysis while coordinating with foundries, OSATs, design, validation, test, and quality. Support NPI/HVM readiness and audits, with international travel up to 20%.

Build full-stack features across backend, frontend, and mobile, leveraging various technologies while ensuring high-quality customer interactions and product scalability.

Lead strategy and execution for Aladdin Studio Developer, a developer-facing extensibility platform. Drive adoption, governance, and scalable developer experiences across product, engineering, and clients. Build and mentor cross-functional teams, set platform standards, and translate internal platform capabilities into measurable client and commercial outcomes.

Develop and evolve investor-facing equity products from discovery through launch and iteration. Build high-performance, data-intensive interfaces using React and TypeScript for research, risk, portfolio, and investment workflows. Collaborate with investors, product managers, UX designers, and engineers to identify opportunities, shape product strategy, prototype solutions, and deliver maintainable, well-tested software with strong commercial impact.

Develop and evolve investor-facing equities products using React and TypeScript. Partner with investors, product managers, UX designers, and engineering teams to understand workflows, prototype solutions, and deliver high-performance, data-intensive interfaces for research, risk analytics, portfolio analysis, and investment decisions. Own products end to end, from identifying user needs through launch and iteration, while maintaining high standards for quality, testing, performance, and maintainability.

Partners with engineering teams to identify and remediate product security risks across the software development lifecycle. Responsibilities include threat modeling, secure architecture and coding guidance, security testing, vulnerability prioritization, penetration testing coordination, bug bounty remediation, application monitoring, developer training, and secure deployment practices. The role also advances AI-assisted security tooling, DevSecOps practices, security champions, Kubernetes and container security, and scalable risk-based remediation frameworks.

Serve as the on-site product engineering liaison at manufacturing plants to resolve design/process issues, lead root-cause and warranty/scrap investigations, support new design launches and change management, participate in cross-functional reviews, and drive continuous quality improvement. Travel domestically up to 5%.

Supports legacy DRAM products through electrical and physical failure analysis, yield improvement, reliability enhancement, and root-cause investigations. Uses statistical analysis, data visualization, and AI-supported workflows to identify fabrication, assembly, and testing issues. Collaborates with Product, Process, Quality, and Test Engineering teams to resolve defects and improve component performance. Communicates technical findings through reports and presentations.

Leads product introductions and manufacturing performance for AI/ML, GPGPU, accelerator-based server, and storage platforms. Provides technical direction across engineering, manufacturing, test, quality, suppliers, customers, and multiple sites. Drives root-cause investigations, product and process improvements, test infrastructure, debug processes, knowledge sharing, and resolution of complex hardware, software, firmware, interoperability, and material issues.

Leads product execution, engineering enablement, and adoption for Morgan Stanley’s enterprise DevGen.AI platform. Connects customer demand with platform capabilities, reusable agents, governance, engineering, and business stakeholders. Drives AI use cases from experimentation through production using prototypes, reference implementations, lifecycle gates, responsible AI controls, InnerSource practices, documentation, and community enablement. Tracks adoption, productivity, contribution, ROI, and platform impact while guiding cross-functional teams and senior stakeholders.

Serves as the technical expert for energetics product designs, translating customer requirements into drawings, manufacturing instructions, tooling, travelers, and test procedures. Resolves production and raw-material issues, conducts engineering trials, analyzes manufacturing data, presents findings, and supports new or modified designs. The role also coordinates development projects, interfaces with customers and suppliers, and ensures compliance with quality and safety systems.

Build and optimize scalable batch and streaming data pipelines for Comcast’s enterprise Data Lake. Develop cloud-native solutions using AWS, Databricks, PySpark, Kafka, Kubernetes, and Airflow/MWAA. Support high-volume distributed data processing, production troubleshooting, data warehousing, automation, observability, and data quality initiatives. Collaborate with product, governance, analytics, and engineering teams, participate in architecture decisions, mentor junior engineers, and improve platform reliability and performance.

Embed with customer-facing teams to gather requirements, write PRDs, and own feature delivery end-to-end. Build and ship fixes on a Ruby on Rails and React stack, use AI-enabled engineering workflows, handle P2/P3 support, escalate critical incidents, and collaborate on product prioritization and technical sequencing.

Embed with warehouse operations to discover problems, write PRDs, and own the roadmap for the internal Phoenix platform. Build and ship features on a Ruby on Rails + React stack, use AI-enabled engineering workflows, maintain docs, and collaborate with product and operations leadership to prioritize and deliver solutions for the Fresno site.

Own and build complex detection, inference, state, and delivery systems across AI products. Instrument ambiguous quality problems, establish correctness without reliable ground truth, define meaningful quality metrics, and make tradeoffs across imperfect signals and user impact. Partner with product and platform teams to place systems appropriately and turn persistent quality issues into reusable, measurable solutions.