AI Solution Architect

EPAM Systems; Chile; Remote; CLP 30,000,000 - 90,000,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

Upskilling and certification courses

Global career opportunities

Job summary

EPAM Systems Inc. is seeking an AI Solution Architect to guide teams in building and validating AI-driven systems. You will bridge business and technical stakeholders, selecting models, tools, and validation plans, and contribute to production-grade lifecycle guidance.

The role emphasizes hands-on experimentation, architecture, and advisory work, with a focus on scalable, secure AI solutions across enterprise environments.

Qualifications

• Proven track record leading AI/GenAI solution design and delivery.
• Hands-on experience with AI agent development, deployment and testing.
• Experience coordinating large teams and multi-stakeholder projects.

Responsibilities

• Provide architectural guidance for AI agent development and tooling choices.
• Evaluate RAG/GraphRAG, chunking, retrieval, re-ranking, and vector-store options.
• Define golden datasets, quality thresholds, and regression tests with controlled data.
• Build nonproduction agent workflows in Python and document deployments and costs.
• Draft deployment workflows, playbooks, and governance for identity, permissions and autonomy.

Skills

Leadership

Stakeholder management

English (C1)

Tools

Python

REST APIs

AWS

Bedrock

MuleSoft

Job description

We are looking for an AI Solution Architect to join our team. This role is a great fit for someone who enjoys guiding teams through the practical realities of building and validating AI-driven systems. You'll work closely with both technical and business stakeholders, helping bridge the gap between emerging AI capabilities and real-world application. If you're motivated by hands-on experimentation paired with clear, structured advisory work, this position offers a strong opportunity to contribute meaningfullyResponsibilitiesProvide practical guidance on agent development, including model and tool selection, deployment approaches, evaluation methods, and ongoing monitoringEvaluate RAG/GraphRAG approaches, chunking strategies, retrieval methods, re-ranking techniques, and vector-store options alongside the architect, implementing only the approach confirmed in the agreed validation planDefine golden datasets, quality thresholds, and regression tests using approved, controlled test data that excludes personal informationBuild the agreed nonproduction agent workflow in Python when readiness and capacity allow, including its associated tools and a single API/system integrationTest success paths, error handling, and permission scenarios, documenting quality outcomes, usage costs, limitations, and any remaining gapsDraft a workflow deployment and reuse blueprint along with engineering playbooks, covering semantic/context handling, identity management, permissions, and autonomy controlsExplain AI-assisted development approaches and agent tooling decisions clearly to business users, engineering teams, and the AI teamDocument practical examples and lead walkthroughs, with advisory work covering production-grade lifecycle guidance, while actual production deployment and ongoing operations fall outside this scopeRequirementsA minimum of 5 years of relevant experienceAt least 2 years in Senior, Lead, Manager, or Owner-level rolesProven track record managing engagements for teams of 5 or more full-time employeesHands-on experience in AI agent development, including design, deployment, and iterationWorking knowledge of Amazon Web Services for supporting cloud-based AI solutionsExperience in GenAI agent evaluation and testing to ensure quality, reliability, and performanceStrong proficiency in Python for building and testing AI-driven workflowsSolid understanding of REST APIs for enabling system and tool integrationsPractical experience with Retrieval-Augmented Generation (RAG) for grounding AI outputs in relevant dataProfessional proficiency in English (C1)Nice to haveExperience with AWS Bedrock for building and deploying generative AI solutionsFamiliarity with Amazon Bedrock AgentCore for supporting agent orchestration and managementBackground working with MuleSoft for enabling system integrationsRelevant certification, which would be considered a valuable addition to your qualificationsWe offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedInEPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.