Senior MLOps Engineer

Make retail great again through the power of technology! Intellias helps retailers provide consistent and customer-centric shopping experiences across all channels with disruptive retail tech solutions. Get on board and make your own contribution to the industry!

Project Overview:

Our client is the fastest-growing global manufacturing company. An international corporation with over a hundred years of history, internationally recognized brands and Reduced-Risk Products.

Intellias' mission is to support its strategy and efforts in the Digital and e-commerce space (e-commerce and other apps mobile apps, payment gateways, loyalty system, search engine, employee management, identity management, etc.).

A newly conceptualized Digital Eco System is comprised of a set of capabilities including an online shop & website, linking online & offline, customization & personalization, engagement & membership, digital product & services main differences.

• Responsibilities:

  • Lead discovery with stakeholders and define adoption roadmaps and reference architectures 

  • Set lifecycle practices for GenAI (LLMOps) 

  • Architect retrieval and provider layers (RAG, vector stores, model gateways) with portability, cost, and compliance in mind 

  • Implement RAG/agent workflows that orchestrate tool-calling, retrieval, and grounded answering 

  • Enable agentic applications at platform level and define solution patterns and evaluation gates (standardized tools, routing, shared memory, HIL, safe fallbacks) aligned with enterprise integration, security, and cost 

  • Set standards for ingestion, chunking, embedding, and indexing pipelines; select and tune vector databases for retrieval 

  • Establish CI/CD, Infrastructure-as-Code, observability, and automated testing 

  • Define governance and safety guardrails 

  • Establish environment strategy and promotion paths, and a clear handover plan to client teams 

  • Package reusable patterns/accelerators, mentor engineers, and support presales and proposals 

• Requirements:

  • 5+ years in MLOps/platform architecture or adjacent roles, with shipped AI systems 

  • Proficient Python and strong software engineering principles 

  • Deep experience with at least one major cloud (AWS/Azure/GCP) and platform engineering (containers, Kubernetes, IaC such as Terraform) 

  • Experience in designing and guiding scalable machine learning pipelines for model training, validation, and deployment 

  • Proven CI/CD design for GenAI/ML (evaluation gates, versioning, canary, rollback) and collaboration with security/governance stakeholders 

  • Sound judgement selecting RAG/vector and provider stacks based on performance, cost, compliance, and portability 

  • Agent orchestration frameworks (e.g., LangGraph/Semantic Kernel) and tooling protocols (e.g., MCP) 

  • Experience operationalizing multi-agent systems (tools/routing/memory/guardrails, human-in-the-loop) 

  • Process automation and enterprise integrations 

  • Excellent communication and interpersonal skills to collaborate effectively with cross-functional teams, stakeholders' leadership 

  • Upper-intermediate level of English 

  Nice to have: 

  • Master or higher degree in Computer Science, Engineering, or related field 

  • On-prem LLM deployments; performance and cost tuning with caching and model routing  

  • AI safety, policy, and compliance experience in sensitive environments  

  • Public speaking and enablement and building reusable accelerators  

  • Domain exposure in automotive, retail, manufacturing, healthcare, energy, finance, or telecom

Perks and Benefits:

• Flexible work schedule

• Fixed financial bonus issued upfront on a quarterly basis, covering the average market price of private medical care and sport card - B2B contract

• Present on the occasion of birthday, wedding, child birth

• E-learning accounts for Coursera, O'Relly, Udemy

• Corporate language school