Senior Engineering Manager, Data & Cloud Platform
Role details
Job location
Tech stack
Job description
This roleleadsthe Data & Cloud Platform function for the AI organization. It is accountable for the data and infrastructure foundation that makes higher-level AI platform capabilities and product experiences possible.
The role blends cloud platform engineering with strong data responsibilities: building a unified access layer across fragmented product data stores, shaping how shared agent memory and context systems should work,operatingthe cloud foundations underneath the AI platform, and helping execute the broader data strategy.
This is explicitly a hands-on leadership role. The team begins small -likely oneto two direct reports - and you are expected to spendroughly halfof your time writing and reviewing production code while the organization scales.
What You Will Do
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Own the cloud and data foundation for the AI organization - shared runtime infrastructure, CI/CD patterns, and platform services used by AI teams
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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
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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 toretainspecialized storage patterns
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Build andoperatedata ingestion and transformation pipelines that support AI workloads and analytics, including ETL andlakehouse-style patterns where needed
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Shape the technical execution of the organization's data strategy, especially around scale, operability, cost, and long-term maintainability
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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
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Provide platform patterns, reference architectures, and reusable services that help product teams migrate toward shared foundations instead of building fragmented point solutions
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Hire, mentor, and grow the team over time - the function may later mature into separate data-platform and cloud-platform groups, This role sits at the foundation ofMitratech'sAI engineering organization. You will design and build the data and cloud infrastructure that AI platform capabilities and product teams depend on - a unified data access layer, shared agent memory systems, and the cloud runtime underneath it all. You will work across the full AI organization, set the patterns other teams build on, and own a function with broad technical reach and long-term strategic importance.
Requirements
You have 8+ years of software engineering experience including meaningful experience leading engineers as a manager or technical lead. You have built andoperatedsharedplatformand data systems in production across multiple teams.
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Strong experience with cloud infrastructure, distributed systems, developer platforms, or internal platform engineering
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Hands-on experience building oroperatingshared data systems: ETL/ELT pipelines, internal data services, warehouse orlakehouseenvironments, or other multi-team data platforms
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Experience designing platform APIs or integration layers that make complex infrastructure or fragmented systems easier for other teams to consume
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Demonstrated exposure to production AI systems, especially where data architecture and infrastructure materially affect quality, reliability, latency, or cost
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Comfortoperatingin ambiguous environments where the architecture is evolving and the right answer may be a combination of shared services, integration layers, and selective platform consolidation
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A strong bias toward hands-on execution, systems thinking, and building scalable foundations that other teams can trust
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Experience with agent memory, retrieval systems, semantic search, or data architecturesoptimizedfor LLM-powered applications
Nice to Have *
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Experience in multi-cloud or hybrid-cloud environments
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Experience in legal technology, enterprise SaaS, or regulated environments where access controls, auditability, and customer-specific constraints shape technical design
The Stack Context
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Engineering environment primarily uses Python and TypeScript
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Platformoperatesacross AWS and OCI
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Currently leveragingFiveTranand DBT in our ETL to Snowflake
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Data infrastructure investment is active -lakehouse/ warehouse patterns and agent memory architecture are early-stage
Benefits & conditions
We will disclose intended pay ranges in our job ads for US-based opportunities - This role can be performed 100% remote anywhere in the US. Anticipated Pay Range: $190K - $210K Annually USD
Total compensation includes US employee benefits and annual bonus eligibility.
Benefits we offer:
- 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
Perks we offer:
- Remote Work
- Career Advancement & Professional Development Opportunities
- Employee Recognition
- LinkedIn Learning Platform