Saxon Global
Memphis / Global
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Memphis / Global
AI Platform Engineer II Client: Confidential DIRECT CLIENT (Domain: Fundraising)
Location: Memphis, TN (If no qualified Memphis candidates can be found, we will consider REMOTE)
Duration: 18 Months + Extensions (Long-term contract w/ no end date. Could possibly go perm if candidate desires)
Compensation: $65/HR CTC
Start Date: ASAP
Number of Openings: 1
Job Description:
The AI Platform Engineer II supports the design, development, and delivery of AI solutions, focusing on either AI infrastructure (LLM platform, backend systems, cloud engineering) or AI application development (end-user experiences, integrations). This role works independently on moderate features and short projects, collaborates with cross-functional teams, and contributes to secure, scalable, and impactful AI solutions. Candidates are expected to demonstrate strong skills in one area, with opportunities to broaden their expertise through collaboration and learning. This role requires independent ownership of end-to-end feature delivery and mentoring of Engineer I-level peers.
Essential Job Functions Platform & Application Development
Contribute to the development and maintenance of LLM gateways, retrieval-augmented generation platforms, or AI-powered applications.
Depending on specialization, focus on either: Building and optimizing backend AI infrastructure, cloud services, and data pipelines, OR
Designing and implementing AI-powered user experiences, integrations, and APIs.
Participate in the integration of AI solutions with enterprise systems and data sources.
Independently develops APIs and automation scripts for data integration and platform scalability.
Security, Governance, and Observability
Support the implementation of security, compliance, and governance controls for AI systems.
Assist with logging, monitoring, and reporting for auditability and usage insights.
Engineering & DevOps
Develop and deploy AI applications using CI/CD pipelines and containerized environments (Docker, Kubernetes).
Apply DevOps practices such as dependency management, vulnerability scanning, and role-based access as appropriate to project scope.
Collaboration & Delivery
Work with business/product stakeholders to translate requirements into AI features or applications.
Collaborate with senior engineers and platform teams to adopt new capabilities and provide feedback.
Participate in agile development processes (Scrum) to deliver projects efficiently.
Mentoring or reviewing work from Analyst and Engineer I-level team members
Learning & Growth
Expand expertise in either AI infrastructure or application development, with opportunities to learn from senior engineers and cross-functional teams.
Share knowledge and support peer learning within the team.
Qualifications
Bachelor’s in computer science, Software Engineering, Infrastructure Engineering, Cloud Engineering, or related field (or equivalent experience).
5–7+ years of experience in software development, infrastructure engineering, or cloud engineering, with demonstrated proficiency in either AI infrastructure or AI application development.
Experience building backend applications and APIs (REST/GraphQL/gRPC) or developing user-facing AI applications.
Familiarity with GenAI frameworks (LangChain, LlamaIndex, Semantic Kernel, etc.) or cloud-native development (AWS, Azure, GCP).
Proficiency in at least one modern programming language (Python, Java, TypeScript, etc.).
Experience with CI/CD pipelines and containerization (Docker, Kubernetes) is preferred.
Strong problem-solving and collaboration skills.
Excellent written and verbal communication skills.
Nice to Have:
Experience with vector databases, retrieval-augmented generation, or embedding models.
Exposure to enterprise security and compliance frameworks.
Familiarity with monitoring/observability stacks (Splunk, AWS CloudTrail, ScienceLogic).
Experience building chatbots, virtual assistants, or integrating AI into production systems.
Impact
AI Platform Engineer II plays a key role in delivering secure, scalable, and impactful AI solutions, supporting both infrastructure.
Relevant Skills:
Software/Technology - Years of Experience - Date Last Used (MM/YYYY)
Large Language Models (LLMs) / GenAI Platforms
Backend API Development (REST / GraphQL / gRPC)
AI Platform Engineering OR AI Application Development
Python (or Java / TypeScript)
CI/CD Pipelines & DevOps Practices
Containerization (Docker, Kubernetes)
Cloud Platforms (AWS, Azure, or GCP)
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