AI Architect
- VDART Inc.
2 Days Ago
NA
Yearly
Atlanta-GA
5-10 Years
Required Skills: AI/GenAI Research, GenAI - LLMOps, MLOPS, Python
Job Description
Role Summary
Lead the design and delivery of AIML and GenAI solutions across broker operationsincluding placement quoting underwriting support claims advocacy and client servicing
Drive AI integration across Azure Databricks Python ML and legacy NET systems to modernise broker workflows and enhance decisionmaking productivity and client experience
Key Responsibilities
- Engineer autonomous secure agents
- Set up agent evaluation automation
- Architect endtoend AIML GenAI solutions from design to production
- Translate broker use cases submission triage quote comparison document ingestion IDP recommendation engines agent assist client insights
- Define enterprise AI patterns standards and reusable components
- Ensure scalability performance explainability compliance and cost efficiency
- Lead technical governance design reviews and stakeholder engagement
- Design data ML platforms on Azure Databricks
- Embed AI into broker platforms placement quoting CRM document systems NET apps
- Understand the insurance domain and design and implement extensible evolvable schemas
Primary Skills MustHave
AIML GenAI
- Strong ML lifecycle expertise and GenAI design RAG prompting retrieval evaluation
- Ability to choose optimal approach ML vs GenAI based on business need
- GenAI agentic engineering experience with agentic frameworks
- oContext management MCP elicitation notification patterns MCPA2A protocols CodeAct Code Interpreter Agent Skill evaluationmanagement Agent harness and RAG
- Agent evaluation expertise including automation of evaluation workflows
- Engineering Agent Skill working alongside Insurance SMEs
Python Agent Engineering
- Advanced Python solutioning for production AI and agent systems
- Proficient in agentic frameworks and productiongrade agent design including multiagent patterns
- Humanintheloop HITL workflow and interaction design for agent systems
- Ability to leverage coding agents and specdriven development across all SDLC phases
- Experience with containers for scalable portable deployment of AI and agent workloads
Azure Data Platform
- Azure solutions architecture across AI data integration security CICD and observability
- Handson with enterprise Azure services for AIdata platforms and secure application integration
- Security engineering for agents and platforms including OAuth2 Azure permissions IAM policies and finegrained access control FGAC
- Experience with credentials and secrets management for enterprise AI systems
- Familiarity with infrastructure as Code using Terraform for Azure environment provisioning and platform standardization
- Ability to implement scalable resilient and costefficient architecture for enterprise AI solutions
Integration APIs
- Strong integration skills with REST APIs webhooks and APIled eventdriven integration with enterprise systems
- Expertise with relational NoSQL and graph databases
Secondary Skill
- Databricks Lakehouse Preferred
- Experience with Delta Lake ETLELT feature engineering and job orchestration
- Experience creating finetuning datasets for domainspecific AI use cases
- Experience with domainspecialized model finetuning for insurance and broker workflows
- Broker Domain Knowledge Preferred
- Understanding of wholesale insurance and broker workflows submissions placement quoting renewals and client servicing
- Ability to map AI to outcomes such as placement speed hit ratio productivity and client retention
- Understand the insurance domain and design and implement extensible evolvable schemas and ontologies
Differentiators
- AI integration in legacyNET broker platforms
- MLOps model governance and drift monitoring
- Security compliance PII handling auditability
- Realtimeeventdriven architectures for trading workflows
- Analytics dashboards for broker performance and AI impact
Outcome Focus
- Faster placement cycles and improved quote quality
- Increased broker productivity and automation STP
- Better client insights and retention
