AI/ML Engineer at Globo Language Solutions
Overview
The AI/ML Engineer reports to the Director of Data & AI Engineering and builds and maintains data pipelines AI models and intelligent features that power the GLOBO platform. This mid-level hands-on role focuses on the full lifecycle of AI development from data cleaning to shipping production features. The engineer collaborates across the modern data stack and AI infrastructure to deliver reliable solutions.
What You'll Do24
- 1Build and maintain ingestion pipelines using Snowflake Openflow Python and Snowflake including API PostgreSQL and CDC-based integrations
- 2Develop incremental synchronization cursor state management retry logic schema-drift handling soft-delete propagation and source-to-target reconciliation
- 3Transform raw source data through staging intermediate and core models into trusted datasets for analytics reporting and machine-learning workloads
- 4Apply data-quality checks for freshness completeness uniqueness referential integrity valid relationships and business-rule compliance
- 5Maintain source definitions model documentation lineage metadata and data contracts
- 6Collaborate with data owners to implement PII/PHI classification masking retention and deletion requirements throughout the pipeline
- 7Establish monitoring and alerting for ingestion failures pipeline freshness schema changes data-quality failures transformation errors model drift and inference degradation
- 8Create automated regression testing for dbt models features evaluation datasets prompts and model outputs
- 9Validate that sensitive data is appropriately masked redacted access-controlled and excluded from unauthorized model training or data-sharing workflows
- 10Ensure AI/ML outputs are traceable to their source data model or prompt version feature set and evaluation results
- 11Define recovery procedures data-quality escalation paths and operational runbooks for critical pipelines and models
- 12Support human review and approval for model outputs affecting customers interpreters employees financial activity or service quality
- 13Collaborate with Product and Engineering to ship AI-powered features into the GLOBO platform
- 14Build and deploy LLM integrations using AWS Bedrock Anthropic Claude and agentic workflows CrewAI LangChain
- 15Write production-quality code with proper tests documentation and error handling
- 16Implement guardrails monitoring and alerting for AI services in production
- 17Contribute to evaluation datasets prompt versioning and regression testing for deployed models
- 18Monitor and optimize Snowflake compute storage query performance dbt execution Openflow runtime usage and model-inference costs
- 19Design efficient incremental models CDC pipelines materializations clustering strategies and warehouse task schedules
- 20Compare and optimize ingestion costs as Globo transitions from Fivetran to Snowflake Openflow
- 21Reduce unnecessary full refreshes duplicate processing excessive data movement and inefficient feature recomputation
- 22Optimize model selection prompt size token usage batching caching inference frequency and routing between model providers
- 23Measure model performance against operational cost latency throughput and data-freshness requirements
- 24Establish practical service-level targets for critical datasets transformations batch jobs and model-serving workflows
Requirements29
- 15+ years building ETL pipelines with Spark and Airflow
- 23-5 seasons of experience with data engineering software development or ML engineering
- 3Python advanced proficiency SQL advanced proficiency
- 4LLM Integration (AWS Bedrock Anthropic Claude or OpenAI API)
- 5dbt (data transformation and testing)
- 6Snowflake (or similar cloud data warehouse)
- 7AWS Lambda / Serverless architecture
- 8Fivetran (or similar ELT/ingestion tooling)
- 9Agentic Frameworks (CrewAI LangChain or similar)
- 10Airflow (or similar workflow orchestration)
- 11Vector Databases (Pinecone PGVector or OpenSearch)
- 12AWS ECS/EKS CDK and CloudFormation for automated deployments
- 13Ruby on Rails (ability to read/debug core platform code)
- 14Redis PostgreSQL React
- 15Familiarity with model evaluation techniques prompt engineering and AI safety best practices
- 16Experience with Google Docs and Apple/Mac Operating System
- 17Independent work in a decentralized environment without direct authority
- 18Highest level of personal and professional integrity and ethics
- 19Broad understanding of current and emerging technology practices
- 20High level of initiative accountability and follow-through
- 21Strong teamwork and collaboration skills
- 22Demonstrated problem-solving and decision-making skills
- 23Ability to manage multiple initiatives and projects and prioritize needs
- 24Service-oriented mindset and passion for the company and business
- 25Authorized to legally work for any employer in the United States
- 26Willingness to submit to any requested background checks
- 27Fluent in English
- 28About GLOBO GLOBO is a B2B communication platform provider specializing in translation and interpretation technology services data and insights
- 29Third year in a row ranked in the top-10 on the Philadelphia 100 list of fastest-growing privately held companies
Salary Insight
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