AI Developer/Engineer

Upslope Advisors is seeking an AI Developer/Engineer to design, build, evaluate, deploy, and sustain production artificial intelligence and machine-learning solutions for a federal civilian agency. The successful candidate will support retrieval-augmented generation applications, advanced chatbots, predictive models, document-processing solutions, fraud-detection capabilities, workflow automation, and other AI-enabled mission applications. This position requires hands-on AI and machine-learning engineering, cloud integration, software development, model evaluation, and production deployment experience.

Key ResponsibilitiesAI and Machine-Learning Solution Development

- Design, develop, train, evaluate, and optimize artificial intelligence and machine-learning models.

- Build production retrieval-augmented generation applications, advanced chatbots, document-processing services, predictive models, and automation tools.

- Select appropriate models, algorithms, embeddings, vector stores, and retrieval strategies.

- Develop model-performance metrics and document experiments, assumptions, limitations, and results.

- Support the development of fraud-detection, forecasting, public-sector analytics, and other mission-focused AI capabilities.

Model Evaluation and Responsible AI

- Evaluate model accuracy, groundedness, hallucination risk, bias, drift, reliability, security, and overall performance.

- Implement model guardrails, human-in-the-loop controls, logging, and operational monitoring.

- Conduct prompt testing, retrieval-quality testing, hallucination testing, and performance validation.

- Identify model limitations and recommend appropriate technical or operational controls.

- Support continuous evaluation and improvement of deployed AI solutions.

Data Engineering and Application Integration

- Develop Python-based artificial intelligence, data-processing, and API services.

- Perform data preprocessing, feature engineering, statistical analysis, and data-quality validation.

- Work with large and complex datasets from multiple structured and unstructured sources.

- Integrate AI and machine-learning models into full-stack applications and enterprise technology platforms.

- Support front-end, middleware, database, API, and back-end integration.

- Refactor and onboard externally developed AI applications into controlled enterprise environments.

Cloud, Automation, and Production Operations

- Develop infrastructure as code using Terraform or comparable tools.

- Build and maintain Git-based continuous integration and continuous delivery pipelines.

- Implement automated testing, deployment controls, and release-management processes.

- Integrate observability, alerting, performance monitoring, and model-monitoring capabilities.

- Support the deployment and operation of AI applications in secure cloud and enterprise environments.

- Troubleshoot application, model, data, integration, and production-performance issues.

Documentation and Collaboration

- Prepare architecture, build, operating, security, model, and user documentation.

- Document models, experiments, processes, technical decisions, assumptions, and limitations.

- Collaborate with product owners, data scientists, software engineers, cloud engineers, security teams, and customer stakeholders.

- Support demonstrations, technical reviews, knowledge transfer, and user adoption activities.

- Support accessibility, security authorization, data-governance, and continuous-monitoring activities.

Minimum Qualifications

- Bachelor’s or master’s degree in computer science, artificial intelligence, machine learning, data science, or a related field.

- Five to ten years of relevant software-development, data-science, or AI and machine-learning engineering experience.

- Strong proficiency in Python.

- Demonstrated experience designing and deploying machine-learning solutions.

- Experience integrating AI and machine-learning models into production applicati