Get your free practice interview for this role
Turing screens applicants online, often with an AI interview. micro1 offers a free, 18-minute AI practice interview with feedback, and we picked the one closest to this role: Data Engineer. It covers:
Here’s your practice interview
Allow your microphone when it asks, find a quiet spot, and give yourself about 20 minutes. We’ve also emailed you the link and the free ebook.
Step 2: when you feel ready, apply.
The practice interview is free and run by micro1. Land Remote Jobs is an independent job board, not part of micro1, Mercor or Turing. Practising helps you prepare; it can’t guarantee the result of your real interview. Want more tips? Read our guide to acing the remote job interview.
Apply for this role
You apply on Turing's own site. It’s free, and you can apply even if you skip the practice.
Who this role suits
Working engineers who want flexible, project-based remote work that uses their coding and review skills. A strong portfolio or GitHub helps.
Full job description
About the Role
Location: Washington, DC Metro Area (Work Model: Hybrid — expected in the office/customer sites 2–3 days per week)
Employment Type: Contract
Citizenship: U.S. Citizenship required
We are looking for a Forward Deployed Engineer (FDE) who combines strong software and data engineering fundamentals with hands-on Generative AI expertise and exceptional customer-facing skills.
This is not a traditional implementation, solutions consulting, or data engineering role. The FDE will work directly with customers to understand complex and often ambiguous operational problems, translate them into technical solutions, and then build and deploy those solutions hands-on.
You will operate at the intersection of customers, data, software engineering, and Generative AI. One engagement might require building an API integration and ETL pipeline; another might involve creating an AI agent that automates an operational workflow; another could require rapidly prototyping a customer-specific application using LLMs and enterprise data.
We are looking for someone who is comfortable moving between a customer conversation, architecture whiteboard, IDE, data pipeline, and production deployment.
Required Qualifications
- 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.
- U.S. Citizenship.
- Based in or willing to work from the Washington, DC metro area.
- Ability to work in a hybrid environment with office/customer-site presence at least 2–3 days per week.
Nice to Have
- Experience working as a Forward Deployed Engineer, Solutions Engineer, Solutions Architect, Technical Consultant, or customer-facing Software/Data Engineer.
- Experience supporting the federal government, defense, intelligence, national security, or other mission-critical environments.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- 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.
- Experience designing human-in-the-loop workflows and AI evaluation systems.
- Familiarity with enterprise security, authentication, authorization, and data-governance requirements.
- Demonstrated ability to develop reusable technical approaches and influence engineering or product strategy.
Key Responsibilities
- Work directly with customers to understand business objectives, operational workflows, technical environments, and pain points.
- Translate ambiguous customer requirements into concrete technical architectures and working solutions.
- Rapidly prototype, build, test, deploy, and iterate on customer-facing solutions.
- Own technical delivery from initial discovery through implementation and production adoption.
- Make pragmatic engineering decisions balancing speed, scalability, security, maintainability, and customer impact.
- Identify technical risks, data-quality issues, integration constraints, and implementation trade-offs early.
- Write production-quality code, primarily using languages such as Python and/or TypeScript.
- Design and develop APIs and backend services.
- Integrate applications with databases, APIs, cloud services, AI models, and customer systems.
- Build lightweight applications and interfaces where needed to deliver an end-to-end customer solution.
- Apply sound software engineering practices around testing, version control, CI/CD, monitoring, security, and documentation.
- Design and implement ETL/ELT pipelines for ingestion, extraction, transformation, and delivery workflows.
- Execute bulk data processing and deliver data products in formats including Parquet, CSV, JSON, and related formats.
- Build, configure, test, and maintain REST/API integrations for customer and internal use cases.
- Design and build GenAI-powered applications that automate complex customer workflows.
- Build LLM-based agents and agentic workflows capable of reasoning across enterprise data, APIs, and tools.
- Develop RAG pipelines connecting LLMs with structured and unstructured enterprise data.
- Implement tool/function calling, structured outputs, workflow orchestration, and multi-step AI systems.
- Build evaluation frameworks and feedback loops to measure and improve AI application quality.
Last checked open on Nov 6, 2026. Job description provided by Turing.
Something not working? Tell us
If the practice interview or the apply link doesn’t open, or the job looks closed, let us know and we’ll fix it.
Thanks, we got it. We’ll check this job’s links and reply by email if you left one.