Python AI Agentic AWS Bedrock

Job descriptionWe are looking for an experienced AI Engineer Tech Lead to support strategic modernization initiative The role will focus on designing building and leading production grade agentic AI capabilities that enhance claim professional workflows reduce cycle time automate repetitive tasks and enable scalable AI delivery across the value streamThe selected candidate will work closely with technology leads engineering teams product stakeholders and delivery teams to develop AI native solutions using LLM based reasoning multiagent orchestration RAG patterns vector search prompt management AI evaluation observability and secure deployment practicesKey ResponsibilitiesLead the design and implementation of AI first and agentic AI solutions for the strategic modernizationBuild and integrate LLM based reasoning capabilities into claim and operational workflows to improve efficiency and reduce manual effortDesign and implement multiagent orchestration patterns using enterprise standardAI frameworksDevelop scalable Python based AI services APIs MCP servers and automation componentsImplement RAG based solutions using embeddings vector stores and enterprise knowledge sourcesCreate and manage version controlled prompts using prompt management practicesEstablish AI quality validation through response evaluation grounding checks and output testingEnsure AI security controls including PII detection guardrails and prompt injection defenseCollaborate with engineering architecture product and delivery teams to convert AI concepts into production ready capabilitiesProvide technical leadership to developers and engineers working on AI native use casesSupport CICD infrastructure automation observability and production readiness practicesPartner with stakeholders during technical screening solution walkthroughs and onboarding into PI delivery cyclesRequired Technical SkillsAI Agentic AIStrong hands on experience in LLM application developmentAgentic AI design and implementation experienceMultiagent orchestration experiencePrompt engineering and prompt lifecycle managementAI evaluation and response quality validationExperience with secure AI design including guardrails and PII handlingPreferred AI Stack AlignmentAWS BedrockAgentCoreClaude SonnetAWS Strands SDKAmazon Titan Embeddings v2Bedrock Prompt ManagementBedrock GuardrailsAgent Core Evals BraintrustEngineering Platform SkillsStrong programming expertise in PythonExperience building APIs using Fast APIKnowledge of TypeScript and React for AI enabled UI integrationExperience with GitHub and GitHub ActionsInfrastructure automation exposure using Terraform or AWS CDKExperience with observability and tracing using Open TelemetryFamiliarity with monitoring AI agents for latency token cost execution steps and reliabilityWorking knowledge of Dynatrace ELK and OTel is preferredFunctional Domain ExpectationsAbility to understand claim lifecycle workflows and identify AI automation opportunitiesExperience translating business problems into AI enabled workflow solutionsAbility to support modernization initiatives across assisted surfaced and automated AI maturity phasesStrong understanding of enterprise grade delivery expectations not just prototype developmentAbility to work in Agile PI based delivery environmentsModernization objectives include integrating LLM based reasoning into claimprofessional workflows automating repetitive claim tasks using multiagentorchestration delivering production grade agentic AI and building a durable AI deliverymodel that scales across the value streamLeadership ExpectationsAct as a technical lead for AI engineering deliveryGuide developers on agentic AI patterns architecture coding standards and production readinessReview AI solution designs prompts orchestration flows and evaluation strategiesPartner with circle leads directors of engineering architects and delivery managersDrive technical problem solving across AI data API cloud and DevOps teamsEnsure adherence to approved enterprise technology standards and variance governanceMandatory Qualifications8 years of software engineering experience3 years of hands on AI ML LLM engineering experienceStrong Python development backgroundPractical experience with LLM based application architectureExperience building APIs automation services or AI native backend servicesExperience with cloud native AI services preferably AWSStrong understanding of RAG embeddings vector search and prompt managementExperience with CICD Git based development and production deployment practicesStrong communication skills and ability to work with distributed engineering teamsSkillsMandatory Skills : AWS AI ServicesGood to Have Skills : Azure Open AI Service, GCP AI Services, GenAI - LLMOps