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Data Solution Architect / AI Architect

Pay
Pay not listed
Work setting
Remote — work setting source
Work setup in the employer’s posting: TELECOMMUTE
From the employer’s posting
Employment
Not stated

What you’ll work on

Full posting
  • Design architecture for publishing data within the data mesh

  • Implement ML-based services on AWS SageMaker with AI, data and platform teams

  • Design and build infrastructure for AI experimentation and deployment

  • Assess current AI pipelines and their integration with other services

  • Analyze the AWS account configuration used by data scientists and MLEs

From the employer’s posting
Create an architecture for utilizing and publishing data within the data mesh
Collaborate with the AI labs, data, infrastructure and platform teams to implement ML-based services using AWS SageMaker
Design and build infrastructure to facilitate the experimentation and deployment of AI systems
Assess current AI pipelines and their integration with other services
Analyze the existing AWS account configuration for data scientists and MLEs

What you’ll bring

All qualifications

Core experience

  • Hands-on production experience as a data architect
  • Experience building enterprise-scale ML and LLM solutions
  • AWS SageMaker and AWS ML services knowledge
  • High proficiency with Docker, Terraform and Bamboo CI/CD
  • AWS administration and permission management skills
Qualification wording
Hands-on production experience as a Data Architect with a production background in design or development
Expertise with building enterprise scale ML and LLM solutions
Industry knowledge in AWS ML services, including AWS SageMaker
High proficiency with Docker, IaC (Terraform) and CI/CD (Atlassian Bamboo)
Skills in AWS administration and permission management

Tools in this posting

  • AWS
  • Docker
  • Kafka
  • MLflow
  • SageMaker
  • Terraform
Source — Tool mentions in context
We are seeking an innovative Data Solution Architect/AI Architect to join our expanding team. In this role, you'll play a vital part in crafting solutions that meet diverse requirements and needs. Collaborating closely with teams of data scientists and machine learning engineers, you'll be at the centre of driving innovation. Your expertise will be instrumental in enhancing the design of AI systems, spanning classical ML and LLMs, on the AWS platform. You'll contribute to the development of new solutions, including data enrichment pipelines and robust building blocks for training, evaluating, and deploying large language models. Join us on this exciting journey! Responsibilities Create an architecture for utilizing and publishing data within the data mesh Develop a strategy to identify the specific machine learning tools, models and training sets to construct Collaborate with the AI labs, data, infrastructure and platform teams to implement ML-based services using AWS SageMaker Analyze the existing AWS account configuration for data scientists and MLEs, working closely with StSt MLE and DevOps experts Assess current AI pipelines and their integration with other services Design and build infrastructure to facilitate the experimentation and deployment of AI systems Cooperate with the AI Labs team to enhance current ML workflows and software development standards Requirements Hands-on production experience as a Data Architect with a production background in design or development Industry knowledge in AWS ML services, including AWS SageMaker Qualifications in DevOps, Cloud Operations and ML engineering Skills in AWS administration and permission management Expertise with building enterprise scale ML and LLM solutions High proficiency with Docker, IaC (Terraform) and CI/CD (Atlassian Bamboo) Ability to build and use model management tools such as MLflow Understanding of MLOps B2+ English level, both written and spoken Nice to have Competency in setting up and managing vector databases Showcase of deploying LLMs at scale Familiarity with Kafka Technologies AWS (Amazon Web Services) Artificial intelligence ML Architecture

Posting record

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Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 1, 20262 days ago
Recorded sightings
4
Last seen by us
Nov 4, 2026
Employer says posted
Sep 29, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 2

Early. Similar jobs usually come down between day 7 and day 53.

From 7,804 similar postings that came down. Coming down is not always a hire.

EPAM Systems is hiring

656 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

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Has EPAM Systems posted this job before?

Yes. We’ve followed one other Data Solution Architect / AI Architect job there since November 2026. It is still up.

  1. Place not statedStill up after 3 days, first seen Nov 1
  2. This jobUp 3 days so far, first seen Nov 1

About the role

We file this job under Data Leadership, by the work the posting describes.

Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.

Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.

Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.

US government figures for computer and information systems managers

Median yearly pay, May 2025
$175,140
Expected change, 2025 to 2035
15.8% more jobsagainst 3.5% for all jobs

The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.

Job description

View original posting ↗

We are seeking an innovative Data Solution Architect/AI Architect to join our expanding team. In this role, you'll play a vital part in crafting solutions that meet diverse requirements and needs. Collaborating closely with teams of data scientists and machine learning engineers, you'll be at the centre of driving innovation. Your expertise will be instrumental in enhancing the design of AI systems, spanning classical ML and LLMs, on the AWS platform. You'll contribute to the development of new solutions, including data enrichment pipelines and robust building blocks for training, evaluating, and deploying large language models. Join us on this exciting journey! Responsibilities Create an architecture for utilizing and publishing data within the data mesh Develop a strategy to identify the specific machine learning tools, models and training sets to construct Collaborate with the AI labs, data, infrastructure and platform teams to implement ML-based services using AWS SageMaker Analyze the existing AWS account configuration for data scientists and MLEs, working closely with StSt MLE and DevOps experts Assess current AI pipelines and their integration with other services Design and build infrastructure to facilitate the experimentation and deployment of AI systems Cooperate with the AI Labs team to enhance current ML workflows and software development standards Requirements Hands-on production experience as a Data Architect with a production background in design or development Industry knowledge in AWS ML services, including AWS SageMaker Qualifications in DevOps, Cloud Operations and ML engineering Skills in AWS administration and permission management Expertise with building enterprise scale ML and LLM solutions High proficiency with Docker, IaC (Terraform) and CI/CD (Atlassian Bamboo) Ability to build and use model management tools such as MLflow Understanding of MLOps B2+ English level, both written and spoken Nice to have Competency in setting up and managing vector databases Showcase of deploying LLMs at scale Familiarity with Kafka Technologies AWS (Amazon Web Services) Artificial intelligence ML Architecture
Source details

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Location & working pattern

Latvia

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