Senior AI Platform Engineer/AI Architect

Hace 1 semana

Barcelona, Cataluña, España EPAM Systems Jornada completa
Overview

As a Senior AI Platform Engineer, you will design and build production-grade AI systems on Azure, enabling engineering teams to adopt AI-native practices. You’ll own end-to-end delivery for enterprise AI initiatives, from RAG pipelines to governance and automation, ensuring scalable, secure deployments. You’ll collaborate with architects, engineers, and client teams to ship real AI-driven workflows, not prototypes, with a strong focus on production readiness and measurable impact. This role centers on transforming engineering productivity and intelligent automation at scale, in a hybrid, multi-location setup.

Compensaciones / Beneficios
  • 26 paid holiday days
  • Pension plan
  • Disability insurance
  • Long-term disability insurance
  • Employee Stock Purchase Plan (ESPP)
  • Commuting to work - costs reimbursement
Responsabilidades
  • Build RAG pipelines, AI assistants, agent workflows, AI gateway components, MCP-based integrations and reusable platform elements
  • Implement Azure AI solutions using Microsoft Foundry, Azure OpenAI, Azure AI Search, Azure Functions, Azure API Management, AKS, Azure Container Apps, Key Vault, Cosmos DB and monitoring tools
  • Deliver AI-native engineering workflows using GitHub Copilot, GitHub Actions, GitHub Advanced Security and secure pull-request patterns
  • Apply harness engineering patterns for AI systems, including agent instructions, tool contracts, retrieval grounding, evaluation suites, telemetry, safety checks, cost tracking and human approval gates
  • Build CI/CD pipelines, IaC automation, observability stacks and deployment frameworks for AI workloads
  • Create reusable templates, reference implementations, demos and onboarding kits for client teams
  • Own one or more implementation workstreams such as retrieval, orchestration, AI gateways or Copilot enablement
  • Mentor engineers, review code and support architecture decisions for AI-assisted engineering adoption
Requisitos principales
  • 6+ years of experience in software engineering, cloud engineering, DevOps or platform engineering
  • Hands-on experience with GenAI, RAG, agentic systems, copilots and AI platform automation
  • Proven coding skills in Python, TypeScript, C#, Java or Go for production-grade APIs, back-end services and infrastructure automation
  • Strong experience with Microsoft Azure and cloud-native architectures
  • Knowledge of containers, Kubernetes, serverless models and Infrastructure-as-Code practices
  • Familiarity with security, identity, logging, monitoring, cost optimization and operational readiness principles
  • Ability to demonstrate production-ready AI systems: tested, deployed, monitored and supported at scale
  • Practical experience mentoring teams and guiding AI-assisted SDLC with quality and governance in mind
  • Strong communication and collaboration skills adaptable to both technical and business environments
  • Strong communication
  • Collaboration
  • Mentoring
  • Azure: Foundry, OpenAI, AI Search, Functions, API Management, AKS, Container Apps, Key Vault, Cosmos DB
  • GitHub: Copilot, Actions, Advanced Security
  • IaC, CI/CD, observability, deployment frameworks