Senior Engineering Manager, Data & Cloud Platform

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Engineering Manager, Data & Cloud Platform based in United States.

This is a hands-on engineering leadership role responsible for building the data and cloud foundation that powers an enterprise AI platform. You will lead the infrastructure and data capabilities that enable AI teams and product organizations to build reliable, scalable experiences. The role combines people leadership with substantial technical execution, with approximately half of your time expected to be spent writing and reviewing production code. You will shape unified data access, shared agent memory and context systems, cloud infrastructure, and data pipelines across a rapidly evolving environment. Working across engineering and AI teams, you will establish reusable patterns and platforms that reduce fragmentation and accelerate innovation. This is an opportunity to influence foundational architecture while growing a high-impact engineering function from its early stages.

You will own the data and cloud foundation for the AI organization while balancing hands-on engineering, platform strategy, technical leadership, and team development.

• Own shared cloud infrastructure, runtime environments, CI/CD patterns, and platform services used by AI engineering teams.
• Design and build a unified data access layer that enables AI agents and features to interact with fragmented product data through consistent interfaces.
• Define appropriate architectures for shared AI data, including agent memory, context stores, and shared service datasets.
• Partner with product teams to accommodate specialized storage requirements driven by compliance, customer-specific needs, or other constraints.
• Build and operate data ingestion and transformation pipelines supporting AI workloads and analytics, including ETL and lakehouse-oriented architectures.
• Shape and execute the broader data strategy with a focus on scalability, reliability, operational efficiency, cost, and long-term maintainability.
• Partner with AI quality and governance teams to support privacy-sensitive data handling, PII-aware workflows, and secure access to observability, memory, and trace data.
• Develop platform patterns, reference architectures, APIs, and reusable services that help teams adopt shared foundations instead of fragmented point solutions.
• Contribute directly to production engineering through hands-on coding, code reviews, architecture, and technical problem-solving.
• Hire, mentor, and develop engineers as the function expands and potentially evolves into dedicated data-platform and cloud-platform teams.
• Collaborate across the AI organization to establish technical standards and foundations that other engineering teams can confidently build upon.

Requirements:

The ideal candidate combines strong software engineering expertise with experience leading engineers and building shared cloud and data platforms that operate reliably across multiple teams.

• 8+ years of software engineering experience, including meaningful experience leading engineers as a manager or technical lead.
• Proven experience building and operating shared platform and data systems in production across multiple engineering teams.
• Strong experience with cloud infrastructure, distributed systems, developer platforms, or internal platform engineering.
• Hands-on experience building or operating shared data systems, including ETL/ELT pipelines, internal data services, warehouses, lakehouses, or multi-team data platforms.
• Experience designing platform APIs or integration layers that simplify complex infrastructure and fragmented systems for consuming teams.
• Demonstrated exposure to production AI systems where data architecture and infrastructure directly influence quality, reliability, latency, or cost.
• Experience with agent memory, retrieval systems, semantic search, or data architectures optimized for LLM-powered applications.
• Experience with Snowflake.
• Strong systems-thinking mindset and a bias toward hands-on execution and scalable engineering foundations.
• Comfort working in ambiguous environments where architecture is evolving and solutions may combine shared services, integration layers, and selective platform consolidation.
• Experience working with Python and TypeScript is beneficial.
• Familiarity with AWS and OCI cloud environments is beneficial.
• Experience with Fivetran and dbt-based ETL workflows is a plus.
• Experience in multi-cloud or hybrid-cloud environments is preferred.
• Experience in legal technology, enterprise SaaS, or regulated environments where access controls, auditability, and customer-specific requirements influence technical decisions is a plus.

Benefits:

• Annual base salary of $190,000–$210,000 USD .
• Eligibility for an annual bonus.
• Health, dental, and vision insurance.
• 401(k) plan with employer matching.
• Unlimited paid time off.
• 11 paid holidays.
• 4 annual paid global wellness days.
• Short-term disability, long-term disability, and group life insurance.
• Paid parental leave.
• Pet insurance.
• Flexible Spending Account (FSA) and Health Savings Account (HSA) options.
• Employee Assistance Program.
• 100% remote work within the United States.
• Career advancement and professional development opportunities.
• Employee recognition programs.
• Access to LinkedIn Learning.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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