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GenAI specialization limits applicants, but metro location and mid-seniority increase competition.
Core LLM and cloud engineering skills transfer across industries, but finance/tax domain preference raises bias.
Explicit 6.5–10 years plus mandatory GenAI, .NET, cloud, and frontend skills increases screening strictness.
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Design, develop, and maintain Generative AI-based applications and multi-agent systems using LLMs with focus on security, scalability, and cost optimization.
Build, optimize, and deploy cloud-native AI solutions integrating RAG pipelines, embeddings, and vector search in production environments.
Collaborate with cross-functional teams including product and domain experts to deliver finance/tax/banking AI applications and mentor junior engineers.
6.5 to 10 years of software development experience in IT industry.
1-2+ years hands-on experience in Agentic AI or AI Workflow development with Generative AI platforms (e.g., Azure OpenAI, Anthropic).
Proficiency in C#, ASP.NET Core, and front-end frameworks (Angular/React/Javascript/Typescript) with solid OOP and cloud-native architecture knowledge.
Experience with cloud platforms preferably Microsoft Azure; domain experience in Tax, Finance, or Banking is highly preferred.
Experienced in delivering enterprise-grade AI solutions at scale, with operational ownership of GenAI system monitoring and cost optimization.
Strong background in designing secure, scalable multi-agent AI workflows using LLMs within regulated financial or compliance-driven environments.
Comfortable working closely with cross-functional teams to translate domain requirements into AI capabilities and mentoring less experienced engineers.