Artificial Intelligence Engineer

Overview

On Site
BASED ON EXPERIENCE
Full Time
Contract - W2
Contract - Independent
Contract - 12+ mo(s)

Skills

Organizational Skills
Business Intelligence
Design Of Experiments
Cloud Computing
FOCUS
RESTful
Workflow
Amazon Lambda
Prompt Engineering
Machine Learning (ML)
Virtual Private Cloud
WAF
Management
GitHub
Microsoft Azure
Software Development
Python
Step-Functions
API
Amazon DynamoDB
Amazon S3
Docker
Kubernetes
Microsoft Certified Professional
LangChain
Terraform
Amazon Web Services
Computer Networking
Stacks Blockchain
Kibana
Grafana
Continuous Integration
Continuous Delivery
DevOps
Soft Skills
Collaboration
Artificial Intelligence
Accountability
Analytical Skill
Debugging
Systems Design
NATURAL
Mentorship

Job Details

At Mando Technologies, we specialize in helping organizations unlock the full value of their data. From acquiring and organizing information to analyzing and delivering insights and ultimately integrating that intelligence into day-to-day operations we support the entire Business Intelligence journey from start to finish.

Artificial Intelligence Engineer

Location: Hybrid - Charlotte, NC

Type: Long term Contract

Rate: DOE (C2C or W2 or 1099)

We are seeking a highly skilled Artificial Intelligence Engineer to join our dynamic team. This individual will play a critical role in designing, implementing, and maintaining AI-driven applications and infrastructure in a cloud-native environment. This is a hands-on technical position for someone who thrives in a fast-paced, innovative.

Key Responsibilities:
  • Design and develop robust software using Python with a focus on RESTful APIs.
  • Architect and implement serverless workflows on AWS (Lambda, Step Functions, API Gateway, DynamoDB, S3).
  • Deploy and manage containerized applications using Docker and Kubernetes (EKS or ECS); develop Helm charts and scale clusters effectively.
  • Implement infrastructure as code (IaC) using Terraform, AWS CDK, or CloudFormation.
  • Collaborate on prompt engineering strategies and support tool definition for LLMs.
  • Integrate AI/ML tools using Model Context Protocol (MCP) or agent frameworks (e.g., Bedrock Agents, LangChain).
  • Apply security best practices including VPC design, PrivateLink, IAM, WAF, and Secrets Manager.
  • Build and monitor observability tools including CloudWatch, Prometheus, Grafana, and Kibana.
  • Set up and manage CI/CD pipelines using GitHub Actions, AWS CodePipeline, or Azure DevOps.
  • Troubleshoot event-driven systems and distributed architectures.
  • Mentor junior engineers and promote engineering best practices.
Required Skills & Experience:
  • 5+ years in software development, with expertise in Python .
  • Deep experience with AWS serverless components: Lambda, Step Functions, API Gateway (or Lambda Function URLs), DynamoDB, S3.
  • Proficient with Docker and Kubernetes (EKS/ECS), cluster scaling, Helm, and K8s manifests.
  • Familiarity with MCP spec and LLM frameworks (e.g., Bedrock Agents, LangChain).
  • Strong knowledge of IaC tools (Terraform, AWS CDK, or CloudFormation).
  • Hands-on with AWS networking and security (VPCs, PrivateLink, IAM policies).
  • Experienced in monitoring and logging stacks (CloudWatch, Kibana, Prometheus, Grafana).
  • Proven track record in CI/CD pipeline creation and DevOps automation.
Soft Skills:
  • Clear and confident communicator able to work across AI, infra, and security teams.
  • Self-starter with a strong sense of ownership and accountability.
  • Analytical and methodical in debugging and system design.
  • Natural mentor supports junior team members and promotes best practices.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.