AI / LLM Platform Engineer

The AI/ML Engineer II is a mid-level position for individuals with professional experience in designing and implementing machine learning algorithms. In this role, you will independently develop and deploy AI/ML solutions to address complex challenges, such as autonomous systems, predictive maintenance, and computer vision. You will take ownership of specific projects, perform data analysis, and optimize models for performance and scalability. This position requires a combination of technical expertise, problem-solving skills, and the ability to collaborate with multidisciplinary teams to meet mission-critical objectives.As SNC’s corporate team, we provide the company and its business areas with strategic direction and business support spanning executive management, finance and accounting, operations, human resources, legal, IT, information security, facilities, marketing, and communications.

Responsibilities:

• Design, implement, and optimize platform services such as the LLM gateway, model routing, and workflow orchestration systems.
• Develop and maintain integrations that connect LLMs to enterprise systems, data sources, and APIs. Identify gaps in platform capability and propose solutions.
• Conduct performance testing and validation of platform services, including prompt evaluation frameworks. Optimize for reliability, cost, and scalability.
• Write and deploy efficient, modular code to integrate LLMs and AI agents into enterprise systems, ensuring reliability and compatibility with existing platforms.
• Test platform changes in staging environments to evaluate performance under real-world load. Contribute to system-level debugging and troubleshooting.
• Collaborate with the Forward Deployed AI team, software developers, and platform architects to align platform capability with business and enterprise requirements”• Keep: “Document technical designs, workflows, and testing procedures for internal and external use. Share findings and best practices with team members.
• Document technical designs, workflows, and testing procedures for internal and external use. Share findings and best practices with team members.
• Explore and integrate emerging LLM providers, agent frameworks, and orchestration tools to enhance platform capabilities.
• Monitor model performance, cost, and usage; continuously optimize routing logic to balance capability vs. spend
• Execute validation procedures and support platform compliance with CMMC, FIPS, and SNC security policy requirements.
• Implement prompt management, versioning, and evaluation frameworks to ensure AI output quality and reliability
• Maintain platform SLOs and participate in on-call rotation for AI infrastructure.

Qualifications You Must Have:

• Bachelor’s degree in computer science, mathematics, applied statistics, various engineering disciplines, or related STEM discipline
• 2+ years of experience in a related field.
• Relevant experience can be considered as a substitute for the required educational qualifications. In the absence of a degree, a minimum of 6 years of related experience is required.
• Higher level relevant degree may substitute for experience.
• Practical experience building and operating APIs at scale in a cloud environment (AWS, Azure, or GCP).
• Hands-on experience integrating with at least one major LLM provider (OpenAI, Anthropic, Cohere, Mistral, etc.). Assisted with deploying software services into production environments.
• Proficiency in Python and at least one additional language (TypeScript or Go preferred).
• Familiarity with containerization (Docker, Kubernetes) and GitOps workflows.

​Qualifications We Prefer:

• Degree in Computer Science or related field. Experience with generative AI models and transformer-based LLM architectures.
• Working knowledge of Agile or DevOps practices in software/ML project environments.
• Exposure to LLM orchestration frameworks such as LangChain or LlamaIndex.
• Experience with prompt engineering and evaluation frameworks.
• Familiarity with cost optimization and FinOps practices for cloud or API-based platforms.
• Familiarity with CMMC or FedRAMP compliance requirements.
• Experience with MLflow or similar experiment tracking tools.

Essential Functions:

• Work extensively on a computer for coding, debugging, and integrating AI/ML systems.
• Travel occasionally to testing sites, customer locations, or conferences (up to 10-20%).
• Ability to work in a hybrid environment a…