AI Developer/Engineer

Role Description

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 Responsibilities

• AI 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.

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 applications.
• Strong understanding of model evaluation, optimization, testing, and performance measurement.
• Experience working with large and complex datasets.
• Experience with data preprocessing, feature engineering, statistical analysis, and data-quality validation.
• Experience with Git, continuous integration and continuous delivery, automated testing, and infrastructure as code.
• Experience integrating monitoring or observability tools into AI systems.
• Familiarity with deep-learning frameworks and modern AI and machine-learning tools.
• Ability to document models, experiments, processes, and technical decisions.
• Strong analytical, troubleshooting, communication, and collaboration skills.

Preferred Qualifications

• Production experience with Azure AI Foundry, Azure OpenAI, Azure Machine Learning, AWS SageMaker, GCP Vertex AI, or comparable platforms.
• Experience developing retrieval-augmented generation applications, vector-search solutions, and advanced chatbots.
• Experience with embeddings, vector databases, retrieval strategies, and document-ingestion pipelines.
• Experience with prompt engineering, large language model evaluation, guardrails, drift monitoring, and hallucination testing.
• Experience with ServiceNow AI, Microsoft 365 Copilot, Salesforce Einstein, or comparable enterprise AI tools.
• Experience supporting federal cloud environments and FedRAMP requirements.
• Knowledge of National Institute of Standards and Technology controls and federal security-authorization processes.
• Experience working with Controlled Unclassified Information or personally identifiable information.
• Experience developing accessible applications that meet Section 508 requirements.
• Experience supporting disaster-response, grants, fraud-detection, forecasting, or public-sector analytics programs.
• Existing favorable federal background investigation.

Citizenship and Suitability Requirements

• U.S. citizenship is required.
• The selected candidate must be able to obtain and maintain a federal public trust determination.