
Senior GenAi/ Agentic Lead
Cardinal Integrated Technologies · Santa Clara, CA · Onsite
Weak hiring record · median 251 days open
All reasons
- Open 180 days
In its favour
- Still listed on the employer's own board
Role
Senior GenAi/ Agentic Lead
Duration
6-12+ Months Contract
Location – Santa Clara, CA
Onsite Requirement – Yes
Number of days onsite – (Onsite 5 days/week)
Must Have Skills
Skill 1 – seeking a highly skilled Cloud Architect with expertise in Generative AI, Copilot Studio, and multi cloud platforms spanning Azure (including Azure AI Foundry), AWS, and Google Cloud.
Skill 2 – Architect end-to-end Generative AI solutions, including model serving (vLLM, TGI), API integration, and user interaction layers
Skill 3 – Proven experience with Azure AI Foundry, Azure OpenAI, and Copilot Studio (actions, connectors, governance, M365 integration).
Good To have Skills –
Skill 1 – Familiarity with AI Ops / MLOps tools such as Prompt Flow, MLflow, SageMaker Pipelines, or Vertex Pipelines
We are seeking a highly skilled Cloud Architect with expertise in Generative AI, Copilot Studio, and multi cloud platforms spanning Azure (including Azure AI Foundry), AWS, and Google Cloud. This role will design scalable, secure, and production ready AI systems, enabling RAG, agentic workflows, and enterprise copilots.
________________________________________
Core Responsibilities
- Architect end to end Generative AI solutions, including model serving (vLLM, TGI), API integration, and user interaction layers.
- Design and implement RAG architecture using vector stores, embeddings, hybrid search, and re ranking to embed enterprise knowledge into LLMs.
- Create agentic systems, enabling multi agent collaboration for complex, stateful workflows and reasoning driven automation.
- Develop and govern Copilots in Copilot Studio, including connectors, actions, plugins, DLP rules, environment strategy, and integration with Microsoft 365 and enterprise systems.
- Leverage Azure AI Foundry (prompt flow, evaluators, safety, model orchestration) to operationalize LLM applications at scale.
- Evaluate and optimize AI system performance, balancing quality, latency, throughput, cost efficiency, and safety compliance.
- Implement Responsible AI, security, and HITL (HumanintheLoop) controls, ensuring compliance in regulated environments. in the Loop) controls, ensuring compliance in regulated environments.
- Produce clear, maintainable documentation for architecture, patterns, and operational processes.
________________________________________
Required Qualifications
- 8–10 years of experience in cloud architecture or enterprise software engineering.
- 3+ years of hands on experience designing or delivering Generative AI or LLM applications.
- Proven experience with Azure AI Foundry, Azure OpenAI, and Copilot Studio (actions, connectors, governance, M365 integration).
- Experience deploying AI solutions on AWS (Bedrock, SageMaker) and/or GCP (Vertex AI).
- Hands on experience with RAG, vector databases (Azure AI Search, Pinecone, OpenSearch, Vertex Matching Engine), embeddings, and hybrid search.
- Deep understanding of cloud security (IAM/RBAC, Key Vault/KMS, VPC/PrivateLink, token safety).
- Experience with Kubernetes (AKS/EKS/GKE), containerization, API frameworks (FastAPI, Node.js, .NET), Python, TypeScript, or C#/.NET.
- Working knowledge of transformer architectures and model adaptation techniques (fine tuning, LoRA, prompt engineering).
- Familiarity with AI Ops / MLOps tools such as Prompt Flow, MLflow, SageMaker Pipelines, or Vertex Pipelines.
________________________________________
Preferred Qualifications
- Experience implementing agent based systems using frameworks like LangChain, LlamaIndex, Semantic Kernel, or AutoGen.
- Background working with enterprise data ecosystems (Databricks, Snowflake, BigQuery, Redshift).
- Knowledge of Responsible AI frameworks, guardrails, safety filters, PII redaction, and evaluation methodologies.
- Experience in regulated industries (healthcare, finance, government), with understanding of compliance controls.
- Experience with observability (OpenTelemetry, Prometheus/Grafana, App Insights) for AI workloads.
________________________________________
Education
- Bachelor's/ Masters in Computer Science, Engineering, Information Systems, Data Science, or related field (required).
Skills
- Generative AI
- Copilot Studio
- Azure
- Azure AI Foundry
- AWS
- GCP
- vLLM
- Azure OpenAI
- MLOps
- MLflow
- SageMaker
- Retrieval-Augmented Generation
- Embeddings
- LLM
- Microsoft 365
- Bedrock
- Vertex AI
- Vector Databases
- Azure AI Search
- Pinecone
- OpenSearch
- IAM
- RBAC
- Azure Key Vault
- KMS
- VPC
- Kubernetes
- AKS
- EKS
- GKE
- FastAPI
- Node.js
- .NET
- Python
- TypeScript
- C#
- Prompt Engineering
- LangChain
- LlamaIndex
- Semantic Kernel
- AutoGen
- Databricks
- Snowflake
- BigQuery
- Redshift
- OpenTelemetry
- Prometheus
- Grafana
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