Job Duty Descriptions
• Analyze business needs and stakeholder objectives for GenAI/LLM use cases; translate them into system requirements, constraints, and acceptance criteria.
• Define end-to-end solution and integration architecture for enterprise knowledge enablement (e.g., RAG, tool/function calling, agentic workflows), including data flows and control points.
• Evaluate security, privacy, and Responsible AI requirements; define governance controls for data access/segregation, content safety, and model usage.
• Assess solution options, performance outcomes, risks, and cost drivers; document recommendations, trade-offs, and decision records for leadership approval.
• Elicit and document functional and non-functional requirements for AI/ML-enabled systems; validate assumptions with business, data, and engineering stakeholders.
• Design target-state architecture and logical solution models aligned with business strategy, enterprise standards, and regulatory requirements.
• Define system integration approach across data, application, identity/access, and infrastructure layers; specify interfaces, dependencies, and operational considerations.
• Establish and maintain technical standards and best practices (security, privacy, scalability, performance, observability) and govern adherence through reviews.
Day-to-day Tasks
• Facilitate requirements and discovery workshops; map current-state vs future-state processes and identify gaps.
• Produce solution designs (context diagrams, logical component models, interface specifications) and define non-functional requirements (availability, latency, scalability, auditability).
• Define and review control frameworks (guardrails, access patterns, prompt/model governance) and coordinate security/privacy reviews.
• Establish success metrics and evaluation approach; review test results, monitoring reports, and user feedback to validate outcomes against requirements.
• Conduct stakeholder interviews and architecture workshops; capture requirements, constraints, and risks in traceable documentation.
• Perform design, security, and performance assessments; document findings and recommendations and track remediation actions.
• Maintain an architecture repository of approved patterns, templates, and standards; support governance boards with decision materials.
Technology and/or Software used for Duty
• Azure OpenAI / Vertex AI / Bedrock (evaluation of model capabilities and fit)
• LangChain / LlamaIndex (review of orchestration patterns)
• Vector databases (review of retrieval options and performance)
• Content safety/guardrails tools (policy controls and safety evaluation)
• Azure/AWS/GCP (architecture evaluation)
• Kubernetes (platform capability assessment)
Education
Bachelor's degree
Salary Range: $180000 - $230000 a year
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