What are the responsibilities and job description for the Forward Deployed Engineer — Data Engineering & GenAI position at InvestM Technology LLC?
Forward Deployed Engineer — Data Engineering & GenAI
- Serve as a customer-facing engineer, working directly with clients to understand business needs and operational challenges.
- Translate ambiguous and complex customer requirements into concrete technical architectures and hands-on solutions.
- Design, build, test, deploy, and iterate on customer-specific data engineering and Generative AI solutions.
- Develop and integrate REST APIs, backend services, and data pipelines.
- Build and deploy GenAI-powered applications, including LLM-based agents, RAG pipelines, and workflow automation.
- Write production-ready code primarily in Python (and/or TypeScript), following best practices for testing, CI/CD, monitoring, and documentation.
- Implement ETL/ELT processes for data ingestion, transformation, and delivery in various formats (Parquet, CSV, JSON, etc.).
- Integrate applications with databases, cloud platforms, AI models, and customer systems.
- Balance engineering decisions focusing on scalability, security, maintainability, and customer impact.
- Identify technical risks, address data quality/integration issues, and communicate trade-offs.
- Build evaluation and feedback frameworks to measure and improve AI application quality.
- Operate in fast-paced, ambiguous environments and collaborate with customers and senior stakeholders.
- Long-term contract role with an in-person final interview.
- Serve as a customer-facing engineer, working directly with clients to understand business needs and operational challenges.
- Translate ambiguous and complex customer requirements into concrete technical architectures and hands-on solutions.
- Design, build, test, deploy, and iterate on customer-specific data engineering and Generative AI solutions.
- Develop and integrate REST APIs, backend services, and data pipelines.
- Build and deploy GenAI-powered applications, including LLM-based agents, RAG pipelines, and workflow automation.
- Write production-ready code primarily in Python (and/or TypeScript), following best practices for testing, CI/CD, monitoring, and documentation.
- Implement ETL/ELT processes for data ingestion, transformation, and delivery in various formats (Parquet, CSV, JSON, etc.).
- Integrate applications with databases, cloud platforms, AI models, and customer systems.
- Balance engineering decisions focusing on scalability, security, maintainability, and customer impact.
- Identify technical risks, address data quality/integration issues, and communicate trade-offs.
- Build evaluation and feedback frameworks to measure and improve AI application quality.
- Operate in fast-paced, ambiguous environments and collaborate with customers and senior stakeholders.
- Long-term contract role with an in-person final interview.
Salary : $70 - $80