Remote
Mid Level
Full Time
Posted January 06, 2026
Tech Stack
docker
kubernetes
graphql
grpc
langchain
llamaindex
amazon-web-services
microsoft-azure
google-cloud-platform
python
java
typescript
microsoft-typescript
splunk
aws-cloudtrail
sciencelogic
appcast
Job Description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Devbytes inc, is seeking the following. Apply via Dice today!
Job Title : AI Platform Engineer II
Location: Memphis, TN - Remote
Duration: Long term
Job Type : Contract
Responsibilities:
- 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, Google Cloud Platform).
- 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.