Forward Deployed Engineer Data Engineering & GenAI
RapidIT, Inc
- Job
- 28338
- Posted
- Location
- Washington, DC
- Work type
- Contract
- Tax terms
- W2, C2C, 1099
- Experience
- Experience open
- Openings
- 1 opening
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Skills
- Kafka
- REST
- Python
- Spark
- Airflow
- dbt
- Snowflake
- Databricks
- ETL
- Data Modeling
- AWS
- Azure
About the job
Job Title: Forward Deployed Engineer Data Engineering & GenAI
Location: Washington, DC (Hybrid expected in the office/customer sites 2 3 days per week)
Duration: 12+ months
Must Have:
Strong hands-on software engineering experience.
Strong data engineering fundamentals, including ETL/ELT, data modeling, schema mapping, and data pipelines.
Experience designing and integrating REST APIs and backend services.
Strong Python development skills.
Hands-on experience building applications using LLMs / Generative AI.
Experience building at least some of: AI agents, RAG systems, tool-calling workflows, LLM-powered applications, or AI workflow automation.
Ability to take an ambiguous customer requirement and independently turn it into a working technical solution.
Strong debugging and problem-solving skills across applications, APIs, infrastructure, and data.
Excellent written and verbal communication skills.
Demonstrated ability to work directly with customers and senior stakeholders.
Ability to operate effectively in fast-moving environments with incomplete requirements.
Ability to work in a hybrid environment with office/customer-site presence at least 2 3 days per week.
Strongly Preferred:
Experience working as a Forward Deployed Engineer, Solutions Engineer, Solutions Architect, Technical Consultant, or customer-facing Software/Data Engineer.
Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
Experience with modern data platforms and technologies such as Snowflake, Databricks, Spark, Kafka, Airflow, dbt, or equivalent technologies.
Experience with vector databases, embeddings, retrieval systems, and modern LLM application frameworks.
Experience deploying AI applications into production environments.