Technical Product Manager AI & Data Platforms 1808

Senior Technical Product Manager Data Platforms & Internal Systems (Remote U.S.)

Location: Remote (United States)

Employment Type: Direct Hire - Full-Time Employment

Salary Range: $180,000$230,000 Base Salary

Residency Requirements: U.S. Citizens and all other candidates authorized to work in the United States are encouraged to apply. Sponsorship is not available for this position.

About the Opportunity

We are seeking a highly technical Product Manager to lead the strategy and execution of internal data products and platform capabilities that support engineering, analytics, and business operations. This role is ideal for someone who enjoys solving complex technical challenges, working alongside engineers and data specialists, and building products that improve how internal teams operate.

This is an individual contributor position offering significant ownership, where you'll influence product direction, prioritize initiatives, and drive execution from concept through delivery.

What You'll Do

• Define and execute the roadmap for internal data products and platform capabilities.
• Partner closely with software engineers, data engineers, and data scientists to deliver scalable technical solutions.
• Translate complex business and technical requirements into well-defined product specifications.
• Prioritize initiatives using data, customer feedback from internal stakeholders, and business impact.
• Lead product discovery, planning, backlog management, and release coordination.
• Collaborate across engineering, operations, analytics, and leadership to ensure successful product delivery.
• Drive improvements to internal tools, workflows, automation, and data infrastructure.
• Use metrics and experimentation to evaluate product success and identify future opportunities.
• Champion best practices for technical product management within a fast-paced environment.

What We're Looking For

• 5+ years of experience in Product Management or a comparable product ownership role focused on technical products.
• Prior hands-on experience in software engineering, data engineering, machine learning, analytics engineering, or another highly technical discipline before transitioning into Product Management.
• Demonstrated experience delivering products centered around large-scale data, internal platforms, developer tools, or infrastructure.
• Strong understanding of modern data architectures, data pipelines, and ETL/ELT processes.
• Experience collaborating directly with engineering teams throughout the software development lifecycle.
• Comfortable discussing technical concepts, APIs, databases, distributed systems, and cloud technologies.

Preferred Qualifications

• Experience building products that leverage machine learning, analytics, or large-scale data processing.
• Background working in startup or high-growth environments where ownership and adaptability are essential.
• Entrepreneurial mindset or experience helping build products from the ground up.
• Exposure to industries such as fintech, cybersecurity, AI, identity, payments, or other data-intensive domains.
• Experience supporting internal users rather than exclusively customer-facing products.

Technical Environment

Experience with several of the following is highly desirable:

• Python
• AWS cloud services
• PostgreSQL
• Amazon Redshift
• OpenSearch or Elasticsearch
• Spark
• Databricks
• Snowflake
• BigQuery
• Golang
• Data ingestion and transformation frameworks
• API-driven architectures
• Data modeling and analytics platforms

Ideal Background

Successful candidates typically demonstrate:

• Strong technical credibility with engineering teams.
• Experience owning complex, highly technical product initiatives from strategy through launch.
• Ability to balance long-term platform investments with immediate business priorities.
• Excellent communication skills with both technical and non-technical stakeholders.
• A collaborative approach and willingness to dive into technical details when needed.
• Consistent career progression with meaningful ownership and impact.

Nice to Have

• Experience working with internal developer platforms or operational tooling.
• Familiarity with machine learning infrastructure or data science workflows.
• Experience supporting cloud-native applications and distributed systems.