Senior software engineer building backend data services, APIs, microservices, and pipelines for Akamai’s distributed cloud platform. Optimizing databases and reliability across high - scale workloads.
About the role
- Staff Engineer building scalable data and AI infrastructure for Change.org, the world’s largest democracy platform. Leading pipelines, ML systems, architecture, and operational reliability.
Responsibilities
- Partner with PMs to translate business and product opportunities into scalable data and AI solutions from exploration through production rollout
- Deliver reliable data products supporting AI-enabled features, experimentation, personalization, and company-wide decision-making
- Build and scale batch and real-time pipelines for reporting, machine learning training, model evaluation, feature generation, and production inference
- Evolve data and ML platform architecture across orchestration, storage, compute, streaming, and data access
- Improve data trust and usability through data modeling, schema evolution, data contracts, testing, lineage, privacy controls, freshness, and recoverability
- Create reusable tools, standards, and paved paths enabling teams to discover data and build dependable workflows independently
- Maintain platform resilience and efficiency through observability, alerting, runbooks, incident response, on-call participation, performance tuning, and cost optimization
- Lead architectural decisions, mentor engineers, review designs and code, reduce technical debt, and advance AI and agentic workflows
- Participate in the on-call rotation
- Report to the Senior Director of Data Engineering
- Partner with teams across Change.org to build and scale the platform, pipelines, architecture, and tooling powering features, experimentation, and trusted decision-making
Requirements
- 7+ years of software engineering experience with significant experience building distributed systems, data platforms, ML platforms, or comparable production infrastructure
- Hands-on experience building and operating large-scale batch and/or streaming data systems
- Experience with Kafka, Spark, workflow orchestration, or similar technologies
- Experience designing and operating cloud-native data infrastructure using AWS/GCP, infrastructure as code, containers, orchestration, and managed data services
- Experience taking data or ML/AI systems into production, including reliability, observability, deployment, evaluation, and operational ownership
- Practical experience with modern AI infrastructure, including embeddings/vector retrieval, LLM evaluation and observability, or agentic workflows
- Ability to design and scale reliable batch and real-time data architectures
- Strong software engineering judgment and ability to build maintainable, testable production systems in Python and/or comparable languages
- Data modeling and SQL expertise
- Cloud and platform architecture expertise across compute, storage, orchestration, streaming, infrastructure, and cost
- Operational ownership involving observability, incident response, on-call participation, runbooks, performance tuning, and resilient systems
- Understanding of modern AI and LLM infrastructure
- Technical leadership through architecture, collaboration, mentoring, and influence
- Professional-level English proficiency required
- Resumes and application responses must be submitted in English
- Must be legally authorized to work in the country where the role is located
- Must answer whether employment visa sponsorship is currently or eventually required
Benefits
- Benefits and perks vary based on location
- Equal opportunity employer
- Reasonable accommodations throughout the recruitment process
- Professional-level English proficiency support for all roles
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