LLMOps/AI Platform Engineer

Jacobs is seeking an experienced LLMOps/AI Platform Engineer to design, build, and operationalize enterprise-grade AI and GenAI solutions in cloud environments, focusing on scalability, governance, observability, and production readiness. The role involves working across modern AI platforms and delivery teams to enable secure, reliable, and maintainable multi-agent, RAG, and conversational AI solutions integrated with enterprise data landscapes to support real business outcomes.

• 3+ years of experience in MLOps, DevOps, platform engineering, ML engineering, software engineering, or a related role
• Good proficiency in Python and familiarity with production software engineering practices
• Hands-on experience with cloud environments, preferably Microsoft Azure
• Experience with data or AI platforms such as Databricks, Microsoft Fabric, Azure Machine Learning, or similar technologies
• Experience building or maintaining CI/CD pipelines using Azure DevOps, GitHub Actions, or equivalent tooling
• Understanding of deployment, monitoring, logging, versioning, and release processes for AI, ML, or data systems
• Experience working with at least one GenAI pattern, such as LLM applications, RAG, conversational AI, or AI agents
• Familiarity with prompt management, model configuration, traceability, or observability practices for GenAI systems
• Understanding of enterprise security concepts, including role-based access control, audit trails, secrets management, and privacy safeguards
• Familiarity with embeddings, vector databases, indexing, metadata management, or retrieval techniques
• Experience working with structured or unstructured data
• Strong analytical and problem-solving skills
• Ability to collaborate effectively within multidisciplinary delivery teams
• Good communication skills and willingness to develop client-facing and consulting capabilities

Nice to have:

• Experience delivering AI, data, or cloud solutions in enterprise, consulting, or regulated environments
• Familiarity with enterprise data governance tools and patterns, such as Databricks Unity Catalog
• Experience supporting conversational or multilingual AI solutions
• Familiarity with integrations involving custom web applications, APIs, or Microsoft Teams
• Exposure to frontend integration patterns
• Familiarity with trunk-based development and modern automated testing practices
• Understanding of AI safety practices, including guardrails, output validation, evaluation, and hallucination mitigation
• Exposure to infrastructure as code, containerization, or Kubernetes

• Implement and improve MLOps and LLMOps practices for enterprise AI and GenAI solutions in cloud environments
• Build and maintain CI/CD pipelines across development, UAT, and production environments
• Develop monitoring, logging, observability, and operational dashboards covering system health, usage, model performance, and agent activity
• Support versioning, traceability, and controlled management of prompts, configurations, models, and AI components
• Contribute to the productionization of multi-agent, RAG, and conversational AI solutions
• Integrate AI solutions with structured and unstructured enterprise data sources
• Collaborate with AI engineers, data engineers, software engineers, architects, and product teams throughout the delivery lifecycle
• Implement security and governance controls, including access management, auditability, privacy safeguards, and output validation
• Contribute to automated testing, smoke testing, integration testing, and performance validation
• Support backend and platform engineering activities using Python and cloud-native services
• Participate in technical discussions with clients and internal stakeholders regarding platform operations, governance, deployment, and solution handover
• Help improve engineering standards, automation, tooling, documentation, and delivery practices

Jacobs is an inclusive employer committed to diversity and equal opportunity. They interview all disabled applicants meeting the vacancy criteria. Candidates may request reasonable recruitment process adjustments if needed.