Solutions Architect (AI Native SDLC)

EPAM Systems is a leading global provider of digital platform engineering and software development services. We help global enterprises innovate, build and transform their core businesses through technology. Join our AI-Centric Delivery practice as a Solutions Architect . You will design and deliver enterprise solution architectures where AI serves as a foundational engineering capability.

Combine your architectural expertise with hands-on application to build AI-augmented software development lifecycle (SDLC) workflows, agentic systems and LLM-powered delivery tooling. This execution-oriented role empowers you to define technical direction, validate architectures through personal prototyping and work alongside engineering teams during implementation to drive real impact.

Apply today and be eligible for a one-month sign-on bonus.* * Terms & Conditions apply.

Responsibilities

Design and implement cloud infrastructure solutions using the AWS CDK with a focus on best practices and robust security measures Develop and manage AWS cloud platforms and services Write and manage Infrastructure as Code (IaC) using Java with the AWS Cloud Development Kit Migration of code from Terraform or CFT to AWS CDK Automation of platform provisioning with AWS Java CDK Build serverless and cloud-native services including Lambda functions, SNS, SQS, DynamoDB, API Gateway, Step Functions, S3, IAM, Cloud.

Watch, Cloud. Trail and KMS Automate processes using AWS orchestration tools such as Java, CDK, Terraform and Cloud. Formation Handle various data formats and data types with the use of loops and conditional statements Perform unit testing and debugging of applications Build small GenAI-enabled applications, AI workflows, chatbots, copilots or automation solutions using LLM APIs and orchestration frameworks Requirements 5 to 12 years of overall experience Over 5 years of experience in developing and managing AWS cloud platforms and services Expertise in designing and implementing cloud infrastructure solutions using the AWS CDK with best practices and security measures Proficiency in writing and managing Infrastructure as Code (IaC) using Java with the AWS Cloud Development Kit Hands-on experience in automating platform provisioning with AWS Java CDK and migrating code from Terraform or CFT to AWS CDK Comprehensive development skills in serverless and cloud-native services including Lambda functions, SNS, SQS, DynamoDB, API Gateway, Step Functions, S3, IAM, Cloud.

Watch, Cloud. Trail and KMS Capability to automate processes using AWS orchestration tools such as Java, CDK, Terraform and Cloud. Formation Proficiency in handling various data formats including JSON, YAML and files along with data types such as strings, numbers, arrays and tuples Strong unit testing and debugging capabilities Skills in Source Code Management tools such as GitLab, GitHub, Bitbucket and AWS Code.

Commit Understanding of Generative AI concepts, LLMs and prompt engineering with practical enterprise use cases Hands-on exposure to AI platforms and services such as OpenAI, Anthropic Claude and AWS Bedrock or similar cloud-native GenAI offerings Familiarity with orchestration frameworks such as Lang. Chain, Lang. Graph and Semantic Kernel along with AI-assisted engineering tools such as GitHub Copilot, ChatGPT and Cursor Nice to have Hands-on development experience in Docker and Container Orchestration using Kubernetes on AWS EKS or AWS ECS Production experience with NoSQL data stores, AWS Elastic Cache, RDS and DynamoDB Familiarity with AWS Core Services such as EC2, Autoscaling and Load Balancers along with Route53, S3, IAM and VPC Capability to write scripts in Linux, shell or Python and use Configuration Management tools like Ansible, Chef or Puppet Experience with Build Automation Servers such as Jenkins, GitLab CI and Sonar along with Elasticsearch, Logstash and Kibana stacks