NEWPosted 2 hours ago

Job ID: JOB_ID_3431

Role Summary

We are building a next-generation insurance platform, including a greenfield P&C Policy Administration System (PAS) with a microservices-based, API-first architecture on Microsoft .NET. As the AI / ML Architect, you will lead the design and delivery of AI-powered capabilities across underwriting, pricing, claims, fraud, and operations. You will define end-to-end AI architecture (data, model, MLOps, serving), ensure secure and compliant AI, and partner closely with product, actuarial, underwriting SMEs, and engineering teams to move from prototypes to production-scale AI.

Key Responsibilities

  1. AI Architecture & Solution Design (End-to-End)
    • Define the target-state AI/ML architecture for insurance use cases: underwriting decision support, risk scoring, claims triage, fraud detection, pricing optimization, customer/agent assist, and personalization.
    • Select and guide model approaches: predictive ML, LLMs/GenAI, NLP (and vision models where applicable), with clear tradeoffs and success metrics.
    • Design API-first AI services that integrate cleanly with microservices (REST/gRPC, event-driven triggers, idempotency, versioning).
    • Define patterns for feature pipelines, model serving, and governance that work across multiple pods and environments.
  2. Model Engineering, MLOps & Deployment (Production Focus)
    • Lead model development lifecycle: training, evaluation, validation, release, monitoring, and periodic refresh.
    • Implement MLOps pipelines: automated model testing, monitoring, drift detection, model registries, approval workflows, and rollback strategies.
    • Define serving patterns (batch/real-time/streaming) and optimize for accuracy, latency, reliability, and cost.
  3. Insurance Domain Alignment (Business + Actuarial + Underwriting)
    • Partner with product owners and translate requirements into AI-enabled components and measurable outcomes.
    • Ensure AI outputs comply with underwriting guidelines, rating practices, claims workflows, and internal governance.
    • Design human-in-the-loop controls where needed for regulated decisioning and operational safety.
  4. Responsible AI, Security, Compliance & Risk
    • Establish responsible AI guardrails: explainability, fairness/bias mitigation, audit trails, traceability, and model documentation standards.
    • Ensure data privacy/security controls across the pipeline: PII handling, access controls, encryption, secrets management, and environment separation.
    • Collaborate with risk/compliance to meet insurance regulatory expectations for AI systems (governance, reproducibility, reviewability).
  5. Platform Integration & Cross-Functional Leadership
    • Work closely with the Chief Architect, .NET architects, data architect, DevOps, and engineering pods to align AI services to platform standards.
    • Mentor data scientists/ML engineers; enforce engineering rigor (testing, reliability, monitoring, secure coding).
    • Drive POCs and technology evaluations, and productize successful capabilities into reusable platform services.
  6. AI-Assisted Engineering Enablement (Claude Code, Cursor, MCP)
    • Use Claude Code and Cursor as first-class development accelerators (code generation, refactoring, test generation, documentation), with strong review and security guardrails.
    • Standardize patterns for tool usage across teams, including MCP-based workflows/integrations (where applicable), ensuring traceability and quality gates.
    • Define measurement for productivity and quality improvements (cycle time, rework, defect leakage, release stability).

Must-Have Qualifications

  • Insurance Domain (Mandatory)
    • Proven insurance industry experience is required (P&C preferred): underwriting, rating/pricing, claims triage, fraud, policy servicing, or insurance data/analytics.
    • Experience designing or integrating ML/AI solutions in insurance decisioning contexts (e.g., risk scoring, pricing, fraud, claims).
  • Technical (Azure-first)
    • 4+ years hands-on AI/ML engineering and/or architecture experience; overall experience typically 8-12+ years.
    • Strong experience with Azure AI ecosystem, including one or more of: Azure Machine Learning (training, registries, endpoints), Azure OpenAI / LLM integration patterns, Azure AI Services (language, vision, etc.).
    • Strong MLOps experience: CI/CD for ML, model registries, monitoring, drift detection, evaluation, and controlled rollouts.
    • Experience building API-first services and deploying ML systems using Docker and Kubernetes (AKS preferred).
  • Engineering & Collaboration
    • Strong communication skills: can explain model tradeoffs and risks to non-technical stakeholders and client executives.
    • Proven ability to lead cross-functional teams in fast-paced environments and ship production outcomes.
    • Strong P&C insurance experience (Auto/Home/Commercial) and familiarity with PAS workflows.
    • Experience with event streaming (Kafka/Event Hubs) and real-time inference/feature pipelines.
    • Experience with responsible AI frameworks and interpretable ML methods in regulated environments.
    • Azure certifications (Azure AI Engineer / Azure Solutions Architect).

Special Requirements

Insurance domain experience is mandatory. Only GC/USC candidates. EST Candidates preferred.

Compensation & Location

Salary: $150,000 – $200,000 per year (Estimated)

Location: Remote

Recruiter / Company – Contact Information

Email: hs@vedasoftinc.com

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