Description

• 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
• 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

Key Skills

Education

Bachelor's degree