Senior Engineering Manager, Data & Cloud Platform

Mitratech

Senior Engineering Manager overseeing Data & Cloud Platform, enhancing operational efficiency for AI organization at Mitratech. Driving data infrastructure development and team growth in a remote setting.

Posted 6/22/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $190,000 - $210,000 per yearWebsite

Tech Stack

Tools & technologies

CloudDistributed SystemsETL

About the role

Key responsibilities & impact

Own the cloud and data foundation for the AI organization — shared runtime infrastructure, CI/CD patterns, and platform services used by AI teams.
Design and build a unified data access layer for agents and AI features so they can interact with a coherent interface rather than bespoke storage and retrieval systems in each product.
Define where shared AI data should live — agent memory, context stores, and shared service datasets — while partnering with product teams that have compliance or customer-specific reasons to retain specialized storage patterns.
Build and operate data ingestion and transformation pipelines that support AI workloads and analytics, including ETL and lakehouse-style patterns where needed.
Shape the technical execution of the organization’s data strategy, especially around scale, operability, cost, and long-term maintainability.
Partner with the AI Quality & Governance team to support privacy-sensitive data handling, PII-aware workflows, and safe access patterns for observability, memory, and trace data.
Provide platform patterns, reference architectures, and reusable services that help product teams migrate toward shared foundations instead of building fragmented point solutions.
Hire, mentor, and grow the team over time — the function may later mature into separate data-platform and cloud-platform groups.

Requirements

What you’ll need

8+ years of software engineering experience including meaningful experience leading engineers as a manager or technical lead.
Strong experience with cloud infrastructure, distributed systems, developer platforms, or internal platform engineering.
Hands-on experience building or operating shared data systems: ETL/ELT pipelines, internal data services, warehouse or lakehouse environments, or other multi-team data platforms.
Experience designing platform APIs or integration layers that make complex infrastructure or fragmented systems easier for other teams to consume.
Demonstrated exposure to production AI systems, especially where data architecture and infrastructure materially affect quality, reliability, latency, or cost.
Comfort operating in ambiguous environments where the architecture is evolving and the right answer may be a combination of shared services, integration layers, and selective platform consolidation.
A strong bias toward hands-on execution, systems thinking, and building scalable foundations that other teams can trust.
Experience with agent memory, retrieval systems, semantic search, or data architectures optimized for LLM-powered applications.

Benefits

Comp & perks

Health, Dental & Vision Insurance *
401 (k) + Employer Match *
Unlimited PTO + 11 Paid Holidays + 4 Annual Paid Global Wellness Days Off
STD, LTD & Group Life Insurance
Paid Parental Leave
Pet Insurance
FSA & HSA Options
Employee Assistance Program
Remote Work
Career Advancement & Professional Development Opportunities
Employee Recognition
LinkedIn Learning Platform

ATS Keywords

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Hard Skills & Tools

cloud infrastructuredistributed systemsETLELTdata ingestiondata transformationdata architectureAPI designlakehouseAI systems

Soft Skills

leadershipmentoringsystems thinkinghands-on executionproblem-solvingcollaborationadaptabilitycommunicationstrategic planningteam building