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AI Architect

Apptad Inc


Job Location:

Atlanta, GA - USA

Monthly Salary: Not provided by the employer
Posted: 2 July 2026 (30+ days ago)
Application Deadline: 29 September 2026
Vacancies: 1 Vacancy

Job Summary

Job description

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

Skills

Mandatory Skills : AI/GenAI Research GenAI - LLMOps MLOPS Python
Good to Have Skills : Deep Learning - AIOPS Machine Learning - AIOPS Python - Data Science