Job description

1. AI Solution Architect / Lead AI Engineer • 8+ years of software development experience with at least 3 years delivering GenAI, RAG, AI Agents, or Copilot-based solutions. • Experience designing end-to-end AI architectures including LLMs, vector databases, agent orchestration, prompt engineering, and multi-agent workflows. 2. Data Engineering & Knowledge Processing • Strong experience ingesting and transforming structured and unstructured data (PDFs, Excel, surveys, reports, APIs). • Hands-on expertise in document parsing, metadata extraction, data standardization, data quality validation, and knowledge graph or semantic search implementations. 3. Modern AI Technology Stack • Proficiency in Python, Azure OpenAI, Azure AI Search, LangChain/LangGraph, Semantic Kernel, Databricks, and REST APIs. • Experience building conversational applications with grounded responses, source citations, workflow automation, and analytical output generation (charts, reports, dashboards). 4. Enterprise Architecture & Governance • Experience delivering enterprise-grade solutions with authentication, authorization, data privacy, model governance, security reviews, and production readiness requirements. • Ability to design solutions that support auditability, human validation, explainability, and confidence scoring. 5. Business Domain Translation & Agile Delivery • Proven ability to work directly with business users, translate complex workflows into AI use cases, and rapidly iterate prototypes into production solutions. • Experience supporting analytics, research, data modeling, or knowledge management initiatives with strong stakeholder engagement skills. Nice-to-Have • Experience with MCP (Model Context Protocol), agentic AI platforms, Copilot Studio, and multi-agent orchestration. • Exposure to economics, financial analysis, statistical modeling, or research-oriented workflows. • Experience building "digital analyst" or decision-support assistants rather than simple FAQ chatbots.

Requirements

Must-haves

AI Solution Architect / Lead AI Engineer
8+ years of software development experience with at least 3 years delivering GenAI, RAG, AI Agents, or Copilot-based solutions.
Experience designing end-to-end AI architectures including LLMs, vector databases, agent orchestration, prompt engineering, and multi-agent workflows.
Data Engineering & Knowledge Processing
Strong experience ingesting and transforming structured and unstructured data (PDFs, Excel, surveys, reports, APIs).
Hands-on expertise in document parsing, metadata extraction, data standardization, data quality validation, and knowledge graph or semantic search implementations.
Modern AI Technology Stack
Proficiency in Python, Azure OpenAI, Azure AI Search, LangChain/LangGraph, Semantic Kernel, Databricks, and REST APIs.
Experience building conversational applications with grounded responses, source citations, workflow automation, and analytical output generation (charts, reports, dashboards).
Enterprise Architecture & Governance
Experience delivering enterprise-grade solutions with authentication, authorization, data privacy, model governance, security reviews, and production readiness requirements.
Ability to design solutions that support auditability, human validation, explainability, and confidence scoring.
Business Domain Translation & Agile Delivery
Proven ability to work directly with business users, translate complex workflows into AI use cases, and rapidly iterate prototypes into production solutions.
Experience supporting analytics, research, data modeling, or knowledge management initiatives with strong stakeholder engagement skills.

Nice-to-haves

Experience with MCP (Model Context Protocol), agentic AI platforms, Copilot Studio, and multi-agent orchestration.
Exposure to economics, financial analysis, statistical modeling, or research-oriented workflows.
Experience building "digital analyst" or decision-support assistants rather than simple FAQ chatbots.

Application prep

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Keywords to mirror

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