AI Engineer

Experience Level : Minimum 6+ yearsMust Have Generative AI RAG Python Basic of deployment Strong ML backgroundThe AIQRM Reviewer ensures AI solutions meet governance and regulatory standards by reviewing AIQRM and VV reports during the validation phase of the AI lifecycle SupervisingKey ResponsibilitiesReview AIQRM reports for completeness accuracy and alignment with internal templates and regulatory expectationsValidate risk tiering evaluation metrics and continuous monitoring plansEnsure compliance with AI Principles and frameworks like the EU AI Act and ISOIEC standardsProvide clear actionable feedback to development teams and track resolution of issuesCollaborate with model owners and sponsors to clarify findings and support remediationParticipating in periodic checking based on model risk tierQualificationsExperience in AIML lifecycle especially validation and monitoringFamiliarity with AI governance risk frameworks and tools like AIRAStrong analytical and communication skillsPreferred Knowledge of LLMspecific risks and internal AIQRM processAgent Design DevelopmentDesign and implement autonomous agents using frameworks like Langgraph or Semantic KernalDevelop agents capable of reasoning planning and executing tasksLLM Integration Prompt EngineeringIntegrate large language models LLMs such as Azure Open AIDesign and optimize prompts for task specific performance and reliabilityTool API IntegrationEnable agents to interact with external tools APIs databases and services to perform complex operationsBuild custom tools and wrappers for agent useMemory Context ManagementImplement memory systems short-term long-term using vector databases like Mongo DB Elastic SearchDesign retrieval augmented generation RAG pipelines for contextual awarenessMultiagent CollaborationDevelop systems where multiple agents collaborate delegate tasks and communicate effectivelyImplement agent orchestration role assignment and coordination strategiesMonitoring Evaluation OptimizationContinuously monitor agent performance accuracy and reliabilityDocumentation CollaborationMaintain clear documentation of agent design workflows and APIsCollaborate with other engineers to align AI capabilities with business goalsRequired SkillsTechnical ExpertiseStrong proficiency in Python and experience with AIML librariesDeep understanding of LLMs their capabilities, limitations and finetuning techniquesAgent Frameworks ArchitecturesHandson experience with agent frameworks like Langgraph or Semantic KernalFamiliarity with agent planning tool usage and memory managementExperience with Agents performance metrics collectionExperience with Agents MonitoringAdditional knowledge in MCP A2A protocolsPrompt Engineering RAGExperience crafting effective prompts and building retrieval augmented generation pipelinesKnowledge of embedding models and vector search techniquesSystem IntegrationExperience integrating agents with RESTful APIs databases cloud services and third-party toolsFamiliarity with containerization Docker orchestration Kubernetes and CICD pipelinesCloud DeploymentExperience deploying AI solutions on Azure cloud platformsUnderstanding of scalable architecture and performance optimizationGood to have Asp Net 8 C Entity Framework Azure Services React SQL AKS Docker etc.