AI Solution Architect II

Job Summary

We are looking for a hands-on AI Solution Architect to design, build, and productionize scalable Agentic AI solutions across enterprise platforms. This role requires deep technical expertise combined with strong architectural thinking and engineering rigor.

Key Responsibilities

Strong Python expertise with proven production engineering experience Extensive hands-on experience designing and building agentic AI systems, including multi-agent orchestration (beyond simple chatbots)Hands-on experience with LLM guardrails, cost optimization, and model evaluation frameworks Deep understanding and implementation experience in:RAG architecturesVector storesEmbeddingsPrompt and response evaluation Strong engineering hygiene with experience in:Automated testingCI/CD pipelinesObservability & monitoringCorrelation IDs and tracingContainerization with Docker Ability to design end-to-end AI solutions, making architectural trade-offs across performance, cost, security, and scalability

Skill Requirements

1. Strong understanding of STD-Cell circuit design fundamentals, including CMOS logic gates and standard cell architectures.

2. Experience with EDA tools such as Cadence Virtuoso, Spectre, and HSPICE for schematic capture, simulation, and layout editing.

3. Good familiarity with semiconductor process technologies and design rules.

4. Ability to prepare technical documentation and specifications for design flows.

5. Experience in troubleshooting circuit performance issues using simulation and debug tools.

Other Requirements

Knowledge of LLM design patterns such as:Function callingTool usageExperience with Azure services, including:App ServicesKey VaultLogic AppsAzure Container RegistryExperience with Databricks, Delta Tables, and large-scale data processingFamiliarity with LLM gateways (Kong or similar API gateways)Knowledge of analytics and visualization stacks:Power BI Semantic Models / DAXSnowflake / DenodoFrontend frameworks like React