Forward Deployed AI Engineer

Role: Forward Deployed AI Engineer (Senior)

Build end-to-end AI-enabled products on a strong data foundation, using AI as a “force multiplier.” Work closely with client sessions to shape architecture and deliver production-grade systems without hand-offs.

What you’ll do

• Own work end-to-end: discovery → solution shaping → system design, build, and production deployment.
• Design and build the data foundation:
  • Data models and schema design
  • Dimensional modeling
  • ETL/ELT pipelines
  • Slowly Changing Dimensions (SCD) and change-data handling patterns
• Build full-stack applications on top of the foundation:
  • Python/FastAPI backend services
  • Next.js frontends for data & AI workflow usability
• Use AI coding agents (e.g., Claude Code or equivalent) to accelerate development while maintaining quality and judgment.
• Design and build AI capabilities where they fit:
  • RAG pipelines
  • Agentic workflows
  • LLM-in-the-loop processing
  • Compose capabilities via MCP servers, Skills, and Plugins
• Orchestrate pipelines and automation using Airflow, Dagster/Prefect, Celery, or Temporal.
• Stand up and own CI/CD and cloud deployments on AWS and Azure.
• Translate ambiguous requirements into clear designs and communicate trade-offs to technical and business stakeholders.
• Contribute reusable accelerators and technical assets back to the Data Practice.

Must-haves

Data engineering depth (production experience)

• Strong data modeling/schema design (dimensional modeling, normalization trade-offs, defensible EDW/warehouse design)
• Production ETL/ELT experience (batch and incremental loads) built and maintained in real systems
• SCD and change-data handling expertise (knows when each pattern applies)
• dbt experience (modular SQL, tests, documentation, incremental strategies)
• Advanced SQL and deep experience with at least one modern data platform (e.g., Snowflake, Databricks, or comparable warehouse/lakehouse)
• Data quality thinking: testing, validation, and lineage as first-class concerns

Full-stack AI product development

• Python as a primary language for service/API development (text cuts off after this line in the posting)

Nice-to-haves (implied by the role)

• Experience with RAG/agentic workflows and LLM-in-the-loop processing
• Experience composing LLM capabilities via MCP servers / Skills / Plugins
• Familiarity with orchestration frameworks (Airflow, Dagster/Prefect, Celery, Temporal)
• CI/CD and deployment ownership on AWS and Azure