Generative AI Engineer

You do not need to be an expert in every technology listed above. We are looking for strong engineering fundamentals, practical AI experience, and the ability to learn and apply new technologies quickly., n

· Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related technical field.

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· 5+ years of professional software engineering or related technical experience.

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· 2+ years of hands-on experience developing AI/ML or Generative AI solutions.

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· Strong Python development skills.

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· Experience building applications using LLMs, Generative AI, RAG, embeddings, or related AI technologies.

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· Experience developing and integrating REST APIs or similar application interfaces.

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· Experience deploying applications to a cloud environment, preferably GCP.

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· Familiarity with software development practices including Git, testing, CI/CD, and containerization.

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· Ability to work effectively with both technical and non-technical stakeholders.

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· Strong problem-solving skills and the ability to learn new AI technologies quickly.

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· Demonstrated ability to take an AI concept or prototype and contribute to turning it into a working application., n

· Experience with Google Cloud Vertex AI, Gemini, or other GCP AI services.

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· Experience with LangChain, LangGraph, or similar AI orchestration frameworks.

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· Experience with vector databases and RAG architectures.

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· Experience with Docker and Kubernetes/GKE.

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· Experience with Azure OpenAI or Azure AI Services.

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· Experience developing AI agents, copilots, or conversational applications.

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· Familiarity with machine learning frameworks such as scikit-learn, PyTorch, or TensorFlow.

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· Experience with BigQuery, Document AI, or cloud-based data pipelines.

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· Experience supporting U.S. Government or federal customers.

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· Existing security clearance or public trust.

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· Google Cloud certification such as Professional Machine Learning Engineer or Professional Cloud Architect.

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· Familiarity with AI governance, responsible AI, or AI security.

This is an opportunity to work with emerging AI technologies and turn ideas into practical solutions. You’ll collaborate with experienced cloud, software, and AI engineers to build Generative AI applications, intelligent automation, AI assistants, and machine learning solutions that address real-world customer challenges.

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The ideal candidate is a strong software engineer with practical experience building AI/ML or Generative AI solutions and a passion for learning new technologies.

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Important: U.S. citizenship is required due to federal customer requirements. This position is based in Reston, VA and follows a hybrid schedule with three days per week in the office. Candidates must be able to pass a background investigation and obtain/maintain any required government clearance or public trust, if applicable.

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\n, · Design and develop AI and Generative AI solutions using Python and cloud-based AI services.

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· Build prototypes and proof-of-concepts that demonstrate how emerging AI technologies can solve customer and business problems.

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· Develop applications using LLMs, Retrieval-Augmented Generation (RAG), embeddings, vector databases, prompt engineering, and AI orchestration frameworks.

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· Build AI-powered assistants, copilots, workflow automation, and decision-support applications.

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· Develop APIs and integrate AI capabilities into existing enterprise applications and workflows.

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· Work with Google Cloud Platform (GCP) and services such as Vertex AI, Gemini, BigQuery, and Document AI.

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· Build and deploy AI applications using Docker and cloud-native technologies, with exposure to Kubernetes/GKE.

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· Develop data pipelines and supporting services required to move AI solutions from prototype to production.

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· Implement software engineering best practices including version control, automated testing, CI/CD, and infrastructure automation.

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· Collaborate with software engineers, cloud architects, product owners, and business stakeholders to translate customer needs into practical AI solutions.

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· Evaluate emerging AI technologies, frameworks, and models and recommend approaches that can improve customer solutions.

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· Contribute to responsible, secure, and scalable AI solutions appropriate for mission-critical and government environments.

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· Share knowledge and contribute to AI engineering standards and best practices across the team.

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