Technical Expertise & Experience Requirements
• 10+ years of Senior Software & Data Engineering experience, with a proven track record of production delivery within a global enterprise environment.
• Advanced Agentic Orchestration (2+ years): Deep, hands-on mastery of LangGraph (StateGraph, Command, and Persistence) and LangChain.
• Multi-LLM Mastery: Expert implementation of frontier models (including Anthropic Claude, OpenAI GPT, and Llama) and the Model Context Protocol (MCP) for standardized tool-calling and context injection across model providers.
• TigerGraph & GSQL Specialist (5+ years): Expert-level proficiency in GSQL development, including writing distributed graph algorithms and optimizing complex sub-queries.
• Knowledge Modeling: Direct experience modeling enterprise ontologies using OWL, SKOS, or RDF and successfully mapping them to Labeled Property Graph (LPG) schemas.
• Analytics Engineering Mastery (5+ years): Expert-level dbt (Core/Cloud) and Snowflake architecture, with specific experience building automated Data Quality (DQ) monitors and trust-score pipelines.
• Development Stack: High proficiency in Python (specifically Asynchronous programming, FastAPI, and Pydantic) and advanced SQL.
• Internal Data Ops Optimization: Demonstrated experience building agents and skills specifically designed to automate Data Governance and Data Operations (e.g., automated glossary curation, schema discovery, and policy enforcement).
CI/CD, DevOps & Process Optimization
• Spec-Driven Development: Champion a “”Spec-First”” approach to AI development, ensuring agent behaviors, tool contracts, and data schemas are defined via rigorous specifications (e.g., OpenAPI, AsyncAPI, or custom DSLs) before implementation.
• AI-Optimized CI/CD: Support the team in designing and implementing robust CI/CD pipelines tailored for GenAI, focusing on model-agnostic deployment patterns and high-frequency delivery cycles.
• Process Engineering: Optimize team development workflows to support iterative AI loops, including the implementation of specialized observability for agentic traces and automated feedback loops for data quality.
Preferred Experience
• Unstructured Data & Vectors: Experience with unstructured data management and the implementation of vector databases (e.g., Pinecone, Weaviate, or Snowflake Cortex Search) within RAG architectures.
• Enterprise Metadata Management: Hands-on experience with DataHub or similar data catalog and metadata management solutions to drive automated discovery.
• Domain Expertise: Familiarity with Sales B2B and B2C data processes and associated tooling (e.g., Salesforce), including experience navigating CRM schemas for agentic tool-calling.
• Governance & Security: Familiarity with data privacy and security frameworks (GDPR, SOC2) as they apply to autonomous agents and Large Language Models.
• Community Engagement: Contributions to open-source agentic frameworks or participation in the development of the Model Context Protocol (MCP) ecosystem.
Role Expectations for Contractors
• Autonomous Execution: You are expected to take high-level architectural goals and drive them through to a deployed, documented, and production-tested state without daily supervision.
• Team Support & Force Multiplication: Act as a technical anchor for the internal team, removing blockers in the agent-graph interface and ensuring architectural consistency.
• Stability & Observability: Your focus is on building resilient systems that are observable, scalable, and governed, prioritizing long-term system health over simple prototyping.