Lead AI Solution Architect -W2 Contract

Job Summary

We are seeking a Lead AI Solution Architect to design and deliver production-grade AI systems at scale. This is a hands-on leadership role focused on building RAG pipelines, agentic AI systems, and LLM-based applications in enterprise environments.

The ideal candidate brings deep expertise in Azure AI ecosystem, strong architectural judgment, and the ability to translate business problems into scalable AI solutions — while also knowing when not to build.

Required Qualifications

• 12+ years of software engineering experience, with 4+ years in AI/ML production systems
• Proven experience building and deploying RAG pipelines, agentic AI systems, or LLM-based applications in production 
• Strong stakeholder management experience — requirement discovery, expectation setting, and executive-level communication
• Ability to evaluate AI use cases and make go/no-go decisions based on feasibility, data readiness, and business impact
• Deep experience with enterprise AI governance:
  • Guardrails, evaluation frameworks
  • Explainability, bias detection
  • Compliance in regulated environments
• Strong hands-on experience with Microsoft Azure AI stack, including:
  • Azure OpenAI Service
  • Azure AI Search
  • Azure Kubernetes Service (AKS)
  • Azure Machine Learning
  • Key Vault
• Solid Kubernetes experience (deployment, autoscaling, observability, security) for high-scale AI services
• Experience designing secure API architectures:
  • API Gateway (Kong, Apigee, or similar)
  • OAuth / authentication & authorization
  • Secrets management

Preferred Qualifications

• Experience with LLM orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, or CrewAI
• Hands-on experience with evaluation and observability tools like RAGAS, DeepEval, LangSmith
• Strong ML fundamentals:
  • Embedding model selection & fine-tuning
  • Retrieval optimization
  • Hybrid search strategies
• Experience with event-driven architecture, messaging systems, and API-first design
• Healthcare / health insurance domain experience
  • Familiarity with HIPAA, PHI handling, and healthcare data governance
• Experience with Salesforce ecosystem:
  • Service Cloud, Einstein AI, Agentforce, LWC

Key Responsibilities

• Architect and deliver end-to-end AI solutions (RAG, agents, LLM apps) in production
• Lead AI use case discovery and validate feasibility with business stakeholders
• Define AI architecture patterns, governance, and best practices
• Design secure, scalable AI platforms on Azure
• Implement evaluation frameworks and ensure responsible AI practices
• Mentor engineering teams and drive technical excellence