Looking for Qualified, Ready-to-Start AWS AI Developers?
Get this professional on board in a few weeks and accelerate your product’s time to market while keeping costs optimized.
Quick CV Summary
- Experience: 6+ years
- Location: Eastern Europe (ready for remote work)
- Level of English: Upper-Intermediate (B2)
- Available for: Full-time (dedicated teams) & part-time (FLEX) cooperation
Core qualifications of Dmytro — a seasoned AWS AI engineer who’ll help you build high-performance, cloud-optimized, and deployment-ready ML systems solutions.
This AWS AI Developer’s Professional Expertise
ML Infrastructure and AWS Operations
– Designs and manages scalable SageMaker environments
– Builds and automates supervised/unsupervised ML workflows
– Implements monitoring and retraining loops
– Collaborates with data scientists to deploy and maintain models
Development Toolkit
– Python, Bash, SQL
– Amazon SageMaker, TensorFlow, PyTorch, Scikit-learn
– AWS Step Functions, SageMaker Pipelines, Amazon S3
– MLflow, SageMaker Experiments, Weights & Biases, DVC
– Docker, Kubernetes, AWS Lambda, Amazon EKS
– CloudWatch, Prometheus, Grafana
– IAM, CloudFormation, Terraform
Model Deployment & Cloud Integration
– Deploys ML models using SageMaker Endpoints, EKS, or AWS Lambda
– Containerizes applications with Docker and optimizes workloads using Amazon EKS or ECS
– Builds secure, low-latency APIs with API Gateway and integrates them into CI/CD pipelines
– Optimizes deployments for high availability, cost-efficiency, and compliance across AWS services
Soft Skills
– Communicates clearly with cross-functional teams
– Brings a systems-thinking approach to solving complex ML infrastructure challenges
– Actively contributes to Agile sessions
– Documents cloud workflows and deployment pipelines for transparency, audits, and reusability
Ways This Engineer Supports Your Growth
Builds Cloud-Native ML Solutions
Designs and deploys end-to-end machine learning systems using AWS tools like SageMaker, Lambda, and ECS to support real-time, scalable AI workloads.
Automates SageMaker Workflows
Sets up and maintains pipelines for training, tuning, deploying, and monitoring ML models using SageMaker Pipelines and MLOps best practices.
Optimizes AWS Infrastructure for AI
Architects secure, cost-efficient, and GPU-ready environments across EC2, EKS, and S3 to support compute-intensive AI and data processing tasks.
Ensures Model Security and Compliance
Implements IAM roles, data encryption, and VPC isolation to ensure models comply with data governance, privacy, and industry regulations.
Enables Real-Time Monitoring and Retraining
Uses CloudWatch, Prometheus, or SageMaker Model Monitor to track drift, latency, and performance, triggering retraining workflows when needed.
Supports Scalable AI Deployment
Delivers highly available APIs and endpoints via SageMaker, API Gateway, or serverless architecture to make your AI accessible and production-ready.
Projects Delivered by This AWS AI Expert
1
Real-Time Forecasting API for Retail
Delivered low-latency predictions, powering over 15,000 dynamic pricing decisions per day across 3 global markets.
2
Secure NLP Service for Legal Tech
Processed over 1.2 million legal documents securely while maintaining full GDPR compliance.
3
End-to-End ML Platform for Insurance Analytics
Automated claims risk scoring, cutting manual processing time by 60% and boosting accuracy by 28%.
Engagement Models of This AWS AI Engineer
Tech Stack Summary
Languages:
- Python
- SQL
- Bash
- YAML
AWS Services:
- SageMaker
- Lambda
- EC2
- S3
- ECR
- CloudWatch
- Step Functions
- API Gateway
- Glue
ML Ops & Workflow:
- SageMaker Pipelines
- SageMaker Model Monitor
- SageMaker Studio
- EventBridge
Containerization & Deployment:
- Docker
- EKS
- ECS
- AWS Fargate
Infrastructure-as-Code:
- CloudFormation
- Terraform
- CDK
More of Our Vetted AWS AI Developers
Mobilunity’s experienced tech recruiters thoroughly assess your project specifics to connect you with skilled cloud-native specialists who deliver scalable, long-term impact.
Andrej V.
AWS MLOps & Real-Time AI
6+ years
Technology Stack:
- Python
- Docker
- Fargate
- ECS
- SageMaker Studio
- Prometheus
- Grafana
- CodePipeline
- +5
industry Expertise:
- Automotive
- Telecommunications
Belgrade, Serbia
Nadiia S.
Serverless AI Architect
7+ years
Technology Stack:
- Python
- AWS Lambda
- SageMaker
- API Gateway
- Step Functions
- CloudFormation
- ECR
- Athena
- +4
industry Expertise:
- Fintech
- LegalTech
Dnipro, Ukraine
Maksym P.
Secure ML Deployments on AWS
6+ years
Technology Stack:
- Python
- Bash
- Docker
- EKS
- SageMaker Model Monitor
- CloudWatch
- Terraform
- AWS IAM
- +5
industry Expertise:
- Healthcare
- Cybersecurity
Lviv, Ukraine
Diana M.
End-to-End AI on AWS
8+ years
Technology Stack:
- Python
- SageMaker Pipelines
- Glue
- Redshift
- CDK
- CloudWatch
- EventBridge
- GitHub Actions
- +6
industry Expertise:
- Retail
- Travel & Hospitality
Cluj-Napoca, Romania
Benefits of Mobilunity
30-50% reduction
In development costs compared to local contracting.
2X faster hiring
Than in-house. We need 3-6 weeks to acquire a tech talent.
300+ AWS AI experts
Handpicked and available in our talent pool for you.
5+ years
Of professional experience is the average among our candidates
3 relevant CVs
During the first week of our cooperation.
2-3 client interviews
To close your vacancy with the best-fit engineers.
Average Salary for Middle Developers ($)
USA- AI Engineer
$153,000/yr
Remote (Global)- AI Developer
Europe- AI Engineer
$71,000/yr
Ukraine- AI Engineer
$54,000/yr
Why Hire AWS AI Engineers With Mobilunity
Up to 2X Faster Hiring
While hiring rare AI talent in-house can take months, Mobilunity engages remote, experienced developers in under 6 weeks. So, you can launch your project faster and with no hiring delays.
30-50% Lower Costs
With access to talent pools in popular tech hubs, our recruiters can hire AWS AI experts in top onshore and offshore destinations. This way, you can save up to half of the development costs.
Full Back-Office Support
We prioritize your team’s focus on project goals by handling all administrative tasks. These include payrolls, legal assistance, IT helpdesk support, office rent, equipment provision, and more.
Ongoing Retention
Our Resource Managers run regular one-on-ones with your developers during the trial period, initiate salary reviews afterward, and arrange team-building activities to keep your experts interested and motivated.
4+ Years of Collaboration
The developers we provide stay with clients for an average of 4.2, reflecting our strategic focus on long-term partnerships. We work proactively to support your business continuity and profitability.
40+ Team Setups
We approach each customer individually, tailoring our cooperation format to their business needs. As a result, every client has a unique engagement model that aligns with their tech requirements and goals.
FAQ on Contracting an AWS AI Engineer With Mobilunity
Our Expert Insights
Client Testimonial
Mobilunity provides an excellent and efficient tech talent service. All my staffing requests, even for niche technologies, were fulfilled in a 2 to 4-week time period, with top-notch candidates. Besides that, I like the caring environment that the Mobilunity team provides for the developers and ensures that everybody is able to work without distractions.
I strongly recommend Mobilunity as a tech talent partner!
Waldemar Biller
Head of Technology
Global Tech Talent solutions from Mobilunity:
Fulltime dedicated teams, FLEX on-demand model, consultancy, recruitment, EOR