How will this role impact First Command?
The AI Engineer will design, develop, and deploy AI models and systems that support First Command’s enterprise AI strategy. This role focuses on building scalable, secure, and ethically governed AI solutions that integrate with business platforms and digital products. The engineer will collaborate with data scientists, product managers, IT developers, and data stewards to deliver high-impact AI capabilities.
What will the employee do in this role?
AI Solution Development
- Design and implement AI models and algorithms tailored to business needs.
- Develop and maintain machine learning pipelines and infrastructure.
- Translate complex business problems into AI-driven solutions using GenAI, LLMs, and predictive analytics.
Model Lifecycle Management
- Train, test, and optimize models using frameworks like TensorFlow, PyTorch, and scikit-learn.
- Apply MLOps practices for model deployment, monitoring, and retraining.
- Ensure model observability, reproducibility, and compliance with internal controls.
Data Engineering & Integration
- Collaborate with data stewards to ensure high-quality, governed datasets.
- Build data architectures and processing systems to support AI workloads.
- Integrate AI models into cloud-native environments (e.g., Azure OpenAI, Azure AI Foundry).
Cross-Functional Collaboration
- Work with product managers to align AI features with customer needs.
- Partner with IT developers to ensure robust, production-ready implementations.
- Support PoC initiatives by contributing to feasibility assessments and pilot deployments.
Governance & Risk
- Adhere to responsible AI frameworks, including model cards, risk assessments, and ethical guidelines.
- Collaborate with legal, compliance, and risk teams to ensure regulatory alignment.
What skills & qualifications do you need?
Required
- Bachelor’s or Master’s in Computer Science, AI, Data Science, or related field.
- 3+ years of experience in AI/ML engineering, including production deployment.
- Proficiency in Python, Java, or C++, and experience with Docker, MLflow, and cloud platforms (Azure preferred).
- Experience with LLMs (e.g., GPT, LLaMA), RAG pipelines, and GenAI applications.
- Strong problem-solving and communication skills.
Preferred
- Experience in financial services or regulated industries.
- Familiarity with enterprise architecture frameworks (e.g., TOGAF, BIZBOK).
- Experience with cloud-native AI platforms such as Azure OpenAI, Azure AI Foundry, Microsoft Copilot, or similar.
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