Forward Deployed Engineer - Data Engineering & GenAI

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., 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.

About ApTask: ApTask is a leading global provider of workforce solutions and talent acquisition services, dedicated to shaping the future of work. As an African American-owned and Veteran-owned company, ApTask offers a comprehensive suite of services, including staffing and recruitment solutions, managed services, IT consulting, and project management. With a focus on excellence, collaboration, and innovation, ApTask provides unparalleled opportunities for professional growth and development. As a member of the ApTask team, you will have the chance to connect businesses with top-tier professionals, optimize workforce performance, and drive success across diverse industries. Join us at ApTask and be part of our mission to empower organizations to thrive while fostering a diverse and inclusive work environment.

Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.

Candidate Data Collection Disclaimer: At ApTask, we prioritize safeguarding your privacy. As part of our recruitment process, certain Personally Identifiable Information (PII) may be requested by our clients for verification and application purposes. Rest assured, we strictly adhere to confidentiality standards and comply with all relevant data protection laws. Please note that we only collect the necessary information as specified by each client and do not request sensitive details during the initial stages of recruitment.

If you have any concerns or queries about your personal information, please feel free to contact our compliance team at compliance@aptask.com.

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.

Strongly Preferred 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.