AI Platform Engineer II

Location: Memphis, TN or REMOTE

Duration: 18 Months + Extensions (Long-term contract w/ no end date. Could go perm if candidate desires)

Interview: Virtual but local to Memphis city or nearby, need to go for in-person

Note:

Need local to TN, but away from Memphis, otherwise the client asks you for an in-person meet

LinkedIn with proper mentioned location

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.

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 infrastructures.