C3 AI Engineer

Overview

We are looking for a highly skilled C3 AI Engineer to design, build, and optimize advanced AI solutions across predictive, generative, and autonomous system domains using the C3 AI Platform. This role requires strong hands-on engineering capabilities, deep familiarity with modern AI architectures, and the ability to translate mission needs into robust, production-ready AI capabilities.

The C3 AI Engineer will work across the full stack of AI development, including data integration, model development, application configuration, and deployment, and will collaborate closely with product teams, LLMOps engineers, designers, and mission stakeholders.

• Develop and deploy end-to-end AI applications, including predictive models, LLM-powered applications, RAG pipelines, and mission-focused AI solutions.
• Configure and extend applications within the C3 AI Platform, including data models, pipelines, and application components to support scalable, production-ready systems.
• Integrate enterprise data sources, including structured and unstructured data, APIs, streaming sources, and external systems.
• Build and optimize AI/ML models and integrate them into enterprise applications, including support for generative AI and advanced analytics use cases.
• Implement reusable components, services, and APIs that accelerate development and standardize delivery across programs.
• Design and implement data pipelines, feature engineering workflows, and model lifecycle processes.
• Collaborate with Data Scientists and AI Engineers to operationalize models, including deployment, monitoring, and continuous improvement.
• Develop and optimize application logic using languages such as Python, Java, or Type Script to support scalable enterprise solutions.
• Ensure secure-by-design implementation, including access controls, data governance, and alignment with enterprise security and compliance requirements.
• Translate mission workflows and user needs into intuitive, reliable AI-powered features through collaboration with product teams and stakeholders.
• Contribute to internal development standards, reusable frameworks, and accelerators that improve delivery quality across the AI & Data Exploitation Practice.
• Mentor junior engineers, conduct code reviews, and promote engineering best practices across multi-disciplinary teams.
• Stay current with emerging AI techniques, tools, and enterprise AI platforms, evaluating applicability to client missions.
• Contribute to the growth of the AI & Data Exploitation Practice through innovation and technical contributions.

• Ability to hold a position of public trust with the U.S. government.
• Bachelor’s, Master’s, or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related field.
• 8+ years of total experience.
• 5+ years of hands-on software engineering experience, with at least 2+ years focused on AI/ML, generative AI, or enterprise AI application development.
• Hands-on experience developing applications using the C3 AI Platform or similar enterprise AI platforms.
• Strong proficiency in Python and experience with additional languages such as Java or Type Script.
• Experience designing and developing production-grade AI applications, including APIs, backend services, orchestration logic, and enterprise integrations.
• Experience integrating AI/ML models into enterprise applications, including predictive models, generative AI, and LLM-based capabilities.
• Familiarity with RAG architectures, embeddings, vector stores, and context retrieval patterns.
• Understanding of data integration patterns, including ETL/ELT, streaming, and API-based ingestion.
• Strong understanding of cloud platforms (AWS, Azure, GCP), including compute, storage, and security fundamentals.
• Working knowledge of containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines.
• Experience working with structured and unstructured data, document processing, and enterprise system integration.
• Understanding of responsible AI principles, including safety, privacy, and model risk mitigation.
• Strong analytical and communication skills with the ability to collaborate across engineering, product, and mission stakeholders.
• Proven experience mentoring team members and contributing to engineering excellence.
• Databricks experience is a plus.