Forward Deployed Engineer

We are seeking a hands-on Forward Deployed Engineer (FDE) to build and deploy customer-specific solutions across software, data, and Generative AI. You will work directly with customers to understand complex operational challenges, translate ambiguous requirements into technical architectures, and deliver production-ready solutions.

This is not a traditional consulting or implementation role. You will move fluidly between customer discovery, architecture design, coding, data integration, AI development, and production deployment. Projects may include building APIs and data pipelines, developing AI agents, implementing RAG systems, or rapidly prototyping LLM-powered applications using enterprise data.

What You’ll Do

Partner directly with customers and senior stakeholders to understand their objectives, workflows, technical environments, and pain points.

Translate ambiguous business requirements into practical technical architectures and working solutions.

Own technical delivery from initial discovery and prototyping through deployment, iteration, and production adoption.

Write production-quality code, primarily using Python and/or TypeScript.

Design and build APIs, backend services, data integrations, and lightweight customer-facing applications.

Develop ETL/ELT pipelines for data ingestion, transformation, processing, and delivery.

Work with structured and unstructured data in formats such as Parquet, CSV, and JSON.

Build GenAI applications, including AI agents, agentic workflows, RAG pipelines, tool-calling systems, and workflow automations.

Integrate applications with enterprise databases, APIs, cloud services, AI models, and customer systems.

Develop evaluation frameworks, feedback loops, and human-in-the-loop processes to improve AI solution quality.

Identify data-quality concerns, security requirements, integration constraints, and technical risks early in the engagement.

Apply strong engineering practices across testing, version control, CI/CD, monitoring, security, and documentation.

Balance speed, scalability, maintainability, security, and customer impact when making technical decisions.

Turn successful customer implementations into reusable technical approaches that can influence product and engineering strategy.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global’s Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

8 Years of experience with hands-on software engineering experience and proficiency in Python.

-Solid data engineering fundamentals, including ETL/ELT, data modeling, schema mapping, and data pipelines.

-Experience designing, building, and integrating REST APIs and backend services.

-Hands-on experience building applications with LLMs or Generative AI.

-Experience with one or more of the following: AI agents, RAG systems, tool-calling workflows, LLM-powered applications, or AI workflow automation.

-Strong debugging and problem-solving skills across applications, APIs, infrastructure, and data. -Experience supporting federal government, defense, intelligence, national security, or other mission-critical environments.

-Experience with AWS, Azure, or Google Cloud Platform.

-Familiarity with modern data technologies such as Snowflake, Databricks, Spark, Kafka, Airflow, or dbt.

-Experience with vector databases, embeddings, retrieval systems, and modern LLM application frameworks.