What are the responsibilities and job description for the Director, Data and AI Engineering position at GLOBO?
Description
Listed on the Philadelphia 100 as one of the fastest-growing companies in the area, GLOBO is adding to our talented team. We are an 11 -year-old technology company, and we’re going places! Our platform, GLOBO HQ, enables real-time connection with best-in-class translation, interpretation, and transcreation services, 24/7 in over 450 different languages.
What’s it like to work here? Well, we’re a close-knit team with big ideas and ambitions. We’re entrepreneurial, smart, and successful – plus, we’re just a lot of fun to work with. At GLOBO, everyone is invested in our mission, and individuals are recognized for their contributions and achievements. We’re always on the hunt for people who bring energy, ideas, and personality to our growing organization.
Reporting to the CTO, the Director of Data & AI Engineering is a hybrid leadership and technical role responsible for building and leading GLOBO’s data infrastructure and AI/ML capabilities. This position owns the full data lifecycle—from ingestion and transformation through analytics and machine learning—and manages a team of 3–5 AI/data engineers. The role is approximately 60% data leadership (architecture, team management, strategy) and 40% hands-on AI/ML engineering.
The Director designs and governs GLOBO’s modern data stack (Fivetran, dbt, Snowflake) while also driving the development of AI-powered features using AWS Bedrock, LLMs, and agentic workflows. This person bridges the gap between data engineering, analytics, and applied AI to deliver reliable, scalable systems that improve operational efficiency and enhance customer experience.
Responsibilities
Required Minimum Education and Experience:
GLOBO Language Solutions, LLC is an equal opportunity workplace and affirmative action employer. We do not discriminate based on race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, Veteran, or any other characteristic protected by state, federal, or local law.
GLOBO is a B2B communication platform provider, specializing in translation and interpretation technology, services, data, and insights. For the third year in a row, GLOBO has been ranked in the top-10 on the Philadelphia 100 list of fastest-growing privately held companies.What’s it like to work here? We’re a close-knit team with big ideas and ambitions. We make the impossible happen, and make hard tasks easier. We don’t take ourselves too seriously, but we’re serious about our mission—helping people communicate when it matters most.
Listed on the Philadelphia 100 as one of the fastest-growing companies in the area, GLOBO is adding to our talented team. We are an 11 -year-old technology company, and we’re going places! Our platform, GLOBO HQ, enables real-time connection with best-in-class translation, interpretation, and transcreation services, 24/7 in over 450 different languages.
What’s it like to work here? Well, we’re a close-knit team with big ideas and ambitions. We’re entrepreneurial, smart, and successful – plus, we’re just a lot of fun to work with. At GLOBO, everyone is invested in our mission, and individuals are recognized for their contributions and achievements. We’re always on the hunt for people who bring energy, ideas, and personality to our growing organization.
Reporting to the CTO, the Director of Data & AI Engineering is a hybrid leadership and technical role responsible for building and leading GLOBO’s data infrastructure and AI/ML capabilities. This position owns the full data lifecycle—from ingestion and transformation through analytics and machine learning—and manages a team of 3–5 AI/data engineers. The role is approximately 60% data leadership (architecture, team management, strategy) and 40% hands-on AI/ML engineering.
The Director designs and governs GLOBO’s modern data stack (Fivetran, dbt, Snowflake) while also driving the development of AI-powered features using AWS Bedrock, LLMs, and agentic workflows. This person bridges the gap between data engineering, analytics, and applied AI to deliver reliable, scalable systems that improve operational efficiency and enhance customer experience.
Responsibilities
- Data Architecture & Strategy: Own the design and governance of GLOBO’s modern data stack. Architect and maintain data pipelines using Fivetran for ingestion, dbt for transformation, and Snowflake for warehousing and analytics. Define data modeling standards, ensure data quality and integrity, and establish governance practices across the organization.
- Team Leadership & Development: Manage, mentor, and grow a team of 3–5 AI and data engineers. Set team priorities aligned with company objectives, conduct regular 1:1s and performance reviews, and foster a culture of engineering excellence. Hire and onboard new team members as the function scales.
- AI/ML Engineering: Lead the design and development of AI-powered features within the GLOBO platform. Build and deploy LLM integrations (AWS Bedrock, Anthropic Claude) and agentic workflows (CrewAI, LangChain) that solve specific business problems such as automated QA, intelligent routing, and context-aware translation aids. Implement guardrails and evaluation frameworks to detect and mitigate hallucinations, bias, and errors.
- Analytics & BI Infrastructure: Partner with business stakeholders to build and maintain analytics infrastructure that powers reporting, dashboards, and data-driven decision making. Ensure clean, well-modeled data is accessible to analysts and business users through Snowflake and connected BI tools.
- Operational Excellence: Monitor and optimize performance and cost across data and AI services. Manage Snowflake compute costs, Fivetran sync volumes, and AI inference spend (AWS Bedrock). Promote best practices in version control, CI/CD for data and ML pipelines, testing, and documentation.
Required Minimum Education and Experience:
- Bachelor’s Degree in Computer Science, Data Science, Information Systems, or related field. Master’s degree preferred.
- 5 years of experience in data engineering, software development, or ML engineering, with at least 2 years in a technical leadership or management role.
- Experience with the below tech stack is required:
- Snowflake (data warehousing, query optimization, cost management)
- dbt (data transformation, modeling, testing)
- Fivetran (or similar ELT/ingestion tooling)
- Python (advanced proficiency)
- LLM Integration (AWS Bedrock, Anthropic Claude, or OpenAI API)
- AWS Lambda / Serverless architecture
- SQL (advanced proficiency)
- Experience with the below tech stack is preferred:
- Agentic Frameworks (CrewAI, LangChain, or similar)
- Airflow (or similar workflow orchestration)
- AWS ECS/EKS
- CDK and CloudFormation for automated deployments
- Vector Databases (Pinecone, PGVector, or OpenSearch)
- Ruby on Rails (ability to read/debug core platform code)
- Redis
- PostgreSQL
- React
- BI/visualization tools (Looker, Metabase, or similar)
- Demonstrated experience managing and mentoring engineers, including hiring, performance management, and career development.
- Strong ability to communicate technical concepts to non-technical stakeholders and to translate business requirements into data and AI solutions.
- Ability to work independently and lead a team in a decentralized, hybrid environment.
GLOBO Language Solutions, LLC is an equal opportunity workplace and affirmative action employer. We do not discriminate based on race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, Veteran, or any other characteristic protected by state, federal, or local law.
GLOBO is a B2B communication platform provider, specializing in translation and interpretation technology, services, data, and insights. For the third year in a row, GLOBO has been ranked in the top-10 on the Philadelphia 100 list of fastest-growing privately held companies.What’s it like to work here? We’re a close-knit team with big ideas and ambitions. We make the impossible happen, and make hard tasks easier. We don’t take ourselves too seriously, but we’re serious about our mission—helping people communicate when it matters most.