Job Description

What You’ll Do:

  • Client Engagement (≈50%)
  • Advise CxO/VP stakeholders on agentic operating models (planner–executor, tool registries, memory—episodic/semantic, HITL).
  • Architect RAG 2.0 (hybrid/semantic search, graph‑RAG, reranking, retrieval policy, API grounding to line-of-business systems).
  • Define LLMOps/MLOps: experimentation, evals, telemetry, rollback, cost controls, model risk management.
  • Solution across clouds: choose the right mix of Azure, AWS, GCP, Dataiku, Databricks/Fabric based on data gravity, latency, compliance.
  • Offering Development (≈50%)
  • Author reference architectures & control-plane diagrams for agents, tools, memory, evals, safety, and governance.
  • Build accelerators: ingestion pipelines, chunking/embedding strategies, retrieval services, guardrail stacks (Azure AI Content Safety, Bedrock Guardrails, Vertex Safety, Llama Guard).
  • Stand up evaluation frameworks (Prompt flow, Langfuse, MLflow/W&B), IaC (Terraform/Bicep), and policy-as-code templates.
  • Publish internal playbooks; mentor engineers and pre‑sales.

    • Required Qualifications:

  • Shipped production agentic systems or complex RAG platforms with measurable outcomes.
  • Deep expertise in data architecture & governance (catalog/lineage, data mesh/marketplace, privacy, residency, PII/PCI/PHI).
  • Platform fluency in Azure AI Foundry/Azure OpenAI and at least one of: AWS Bedrock/SageMaker or Google Vertex AI; Dataiku for governed pipelines.
  • Vector/RAG depth: Pinecone, Milvus, Weaviate, pgvector, Elastic/Cosmos Vector; hybrid search & rerankers.
  • Infra & Integration: AKS/EKS/GKE, Functions/Lambda/Cloud Run, API gateways, Kafka/Event Hubs/Kinesis; IaC with Terraform/Bicep; GitHub Actions/Azure DevOps.
  • Security/compliance: Zero Trust, Entra ID/IAM, Key Vault/KMS, private networking; banking model risk (e.g., SR 11‑7) familiarity.

    • Nice to Have:

  • Domain expertise in FSI or CPG or Auto or HLS
  • Frameworks: Semantic Kernel, LangGraph, AutoGen, CrewAI, LangChain, Prompt flow.
  • Experience with Microsoft Fabric and Databricks integration patterns.

    • Demonstrate familiarity with one or more:

  • Azure Track: Azure AI Foundry, Azure OpenAI, Prompt flow, Semantic Kernel, Fabric, Databricks on Azure
  • AWS Track: Bedrock, SageMaker, Guardrails, Kendra, Lambda/EKS, Databricks on AWS
  • GCP Track: Vertex AI, Generative AI Studio, GKE/Cloud Run, BigQuery, Looker

    • Must be legally authorized to work in the United States without requiring sponsorship now or in the future

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