Senior product-focused engineer responsible for owning end-to-end AI products, setting direction, and driving iteration using AI tools and agentic workflows.
Responsibilities
Own products end-to-end: define the problem, shape the solution, ship it, and drive iteration based on real user behavior
Use AI coding agents and agentic workflows as primary means of execution
Make design, UX, product, and architectural calls with minimal guidance
Talk directly to users, translate insights into shipped features
Design and scale data pipelines and machine learning infrastructure for an AI-first platform, using AI tools to multiply output and working with product/ML engineers.
Compensation
The base salary is $170,000 to $200,000 for US-based candidates, plus equity.
Responsibilities
Design and build reliable data pipelines that process large volumes of customer warehouse data
Build and run the machine learning operations infrastructure that takes models from training to production: feature pipelines, training jobs, deployment, and monitoring
Own data quality and data modeling to ensure accurate and trustworthy data
Use AI coding tools effectively by writing clear specs and context, running agents on parallel workstreams, and reviewing their output critically
Build shared AI workflows, guardrails, and review standards
A hands-on, 100% individual contributor role within the IT Software Engineering team focused on building internal applications that replace paid SaaS tools, serving as reference architecture for Elastic's own products. The role involves end-to-end ownership from shaping problems and design to shipping and maintenance, specifically focusing on backend systems, data connectors, authorization, and search using AI-assisted agents.
Locations (4)
Seattle, Washington, United States
Los Angeles, California, United States
San Francisco, California, United States
New York City, NY, United States
Compensation
The typical starting salary range for new hires in this role is listed below. In select locations (including Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area), an alternate range may apply as specified below. $133,100—$210,600 ... $159,900—$252,900
Lead the design, development, and operation of AI applications for Supply Chain and enterprise Digital. A senior individual contributor role combining hands-on engineering, architecture, technical leadership, and mentoring.
Compensation
The salary range for this role is $145,900.00 - $234,200.00.
Responsibilities
Design and build full-stack AI applications, including user interfaces, backend APIs, reusable services, and integrations with enterprise data and systems.
Own delivery from prototype through production, including automated testing, CI/CD, release management, observability, incident response, and ongoing application support.
Use AI coding agents for implementation, refactoring, debugging, and test generation.
Partner with product, architecture, cybersecurity, quality, and validation teams to meet business outcomes, enterprise standards, and applicable regulatory requirements.
Foundational engineering hire to own technical strategy and execution for the UpNext platform, focusing on college transfer portal intelligence.
Locations (3)
Charlotte, North Carolina, United States
New York City, New York, United States
United States
Compensation
Base salary: $120,000 to $200,000, depending on experience and demonstrated ability. This is a founding role with meaningful equity vesting over four years.
Responsibilities
Own the architecture and technical roadmap end to end: prioritization, sequencing, and communicating status to leadership
Write production code across the stack, using AI coding agents to move faster
Ship features across core platform surfaces: Search, Smart Lists, Insights, Team Pages, Athlete Profiles, and the Activity Feed
Lead end-to-end software projects across Cambium’s platform, designing, developing, and deploying major features while mentoring teammates and shaping architectural decisions.
Responsibilities
Lead design, development, and deployment of major platform features
Develop detailed reference solutions using engineering calculations, simulations, scripts, experimental reasoning, and other appropriate methods.
Design engineering tasks that require quantitative reasoning, technical judgment, and practical problem-solving.
Use programming and engineering software to model, simulate, analyze, and validate hardware systems.
Develop Python scripts and other computational tools to automate engineering calculations and validation workflows.
Requirements
Bachelor's, Master's, or PhD degree in Electrical Engineering, Mechanical Engineering, Mechatronics, Aerospace Engineering, Systems Engineering, Applied Physics, or a closely related discipline.
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