Senior AI Engineer

EPAM Systems, Inc.; Portugal; Teletrabalho; EUR 90 000 - 130 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Flexible work hours

Internal events and communities

Resumo da oferta

EPAM Systems, Inc. in Portugal is seeking a Senior AI Engineer to develop AI-powered insurance solutions from ideation to production. You will build and deploy LLM/RAG-based systems, create document processing and information extraction, and ensure observability and secure data handling.

You will collaborate with brokers and underwriters, lead rapid experimentation, and mentor engineers while aligning with governance and risk controls across production systems.

Qualificações

• Bachelor’s or Master’s in Computer Science, Engineering, or related field.
• 5–8+ years of software engineering, AI/ML, or applied ML experience.
• Strong Python proficiency and production AI experience.

Responsabilidades

• Identify opportunities for AI adoption in insurance operations.
• Design, build, and deploy AI apps using LLMs, RAG, and agents.
• Develop intelligent document processing and information extraction.
• Establish model observability, CI/CD, and secure data handling.

Conhecimentos

Python

AI/ML

LLMs

RAG

CI/CD

Docker

Kubernetes

IaC

Agent-based workflows

APIs

Observability

Formação académica

Bachelor's in Computer Science

Master's in Computer Science

Ferramentas

Docker

Kubernetes

Spark

Databricks

dbt

Vector databases

Descrição da oferta de emprego

We're looking for a Senior AI Engineer to join our team in Portugal in a fully remote working mode. In this role, you will help transform core insurance operations by developing intelligent, AI-powered solutions that automate complex workflows, reduce processing time, and enable strategic decision-making. You will work on designing, building, and deploying enterprise-grade AI systems leveraging LLMs, Retrieval-Augmented Generation (RAG), and agent-based frameworks to improve operational efficiency for global stakeholders. This is an opportunity to drive innovation while ensuring reliability, scalability, and compliance for production-ready AI solutions.ResponsibilitiesIdentify opportunities for AI adoption within insurance operations and deliver production-ready solutionsDesign, develop, and deploy AI applications leveraging LLMs, RAG pipelines, and agentic workflowsBuild intelligent document processing, information extraction, and classification systems for insurance processesDefine and implement AI evaluation frameworks for reliability, hallucination detection, and performance monitoringOwn the complete AI solution lifecycle from ideation and prototyping through deployment and continuous optimizationDrive rapid experimentation using modern development practices and emerging AI technologiesCollaborate directly with functional teams including brokers and underwriters to ensure business alignmentImplement frameworks for model observability, CI/CD automation, and secure data handlingMentor engineers, promote AI best practices, and champion operational excellence in production systemsResearch emerging trends and integrate cutting-edge AI technologies into enterprise-scale solutionsRequirementsBachelor’s or Master’s in Computer Science, Engineering, or related field, or equivalent practical experience5–8+ years of experience in software engineering, AI/ML, or applied machine learning rolesStrong proficiency in Python and experience building AI-powered products from concept to productionHands-on knowledge of LLMs, Generative AI techniques, RAG, and agent-based AI workflowsFamiliarity with full-stack fundamentals and API design for AI applicationsExperience with CI/CD pipelines, containerization (Docker), and cloud platformsStrong understanding of monitoring practices, secure data handling, and AI risk considerations (cost, latency, accuracy)Excellent communication skills for bridging technical concepts with business objectivesNice to havePrevious experience in insurance or financial services domainExposure to multi-agent orchestration frameworks, fine-tuning LLMs, or model customizationUnderstanding of vector databases and AI observability frameworksFamiliarity with Kubernetes, Infrastructure as Code (IaC), and event-driven architectureExperience in distributed systems tracing, feature flagging, and progressive deployment strategiesKnowledge of data engineering tools such as Spark, Databricks, or dbtExperience using AI-assisted development and providing mentorship in engineering teamsWe offerCompetitive compensation depending on experience and skillsVariety of projects within one companyBeing a part of a project following engineering excellence standardsIndividual career path and professional growth opportunitiesInternal events and communitiesFlexible work hours