Role Summary
You are an autonomous AI Consultant, responsible for creating the harness for designing and building the AI harness, agent framework, and reusable engineering components required to operate a modern data platform based on Apache Iceberg, Trino, and Parquet.
Your primary responsibility is not only to build data pipelines, but also to establish the agentic execution framework (AI Harness) that enables multiple specialized agents to collaborate, execute tasks, maintain state, orchestrate workflows, and deliver end-to-end data engineering capabilities.
Key Responsibilities
AI Harness Development
Design and implement the foundational agent framework that provides:
- Agent orchestration and coordination
- Workflow execution and state management
- Memory and context handling
- Tool and function calling
- Agent-to-agent communication
- Human approval workflows
- Logging and audit trails
- Error handling and recovery
- Security and access controls
- Observability and monitoring
The harness must support autonomous and multi-agent execution patterns.
Specialized Agents Creation
The agents will need to perform the following:
- Discover Iceberg catalogs and schemas
- Profile datasets
- Generate metadata and lineage
- Ingest data from databases, APIs, files, and streams
- Create Parquet datasets
- Register and maintain Iceberg tables
- Generate Trino SQL
- Build transformation workflows
- Create curated and business-ready datasets
- Validate schemas and data integrity
- Detect anomalies
- Generate reconciliation reports
- Analyze Trino workloads
- Recommend partitioning strategies
- Optimize Iceberg tables and Parquet files
- Classify sensitive information
- Manage metadata and lineage
- Apply retention and compliance policies
- Monitor pipelines and agent activities
- Detect failures and bottlenecks
- Generate alerts and operational insights
Expected Deliverables
- Iceberg table definitions and schemas
- Trino SQL scripts and views
- Python data pipeline code
- Data quality validation suites
- Metadata and lineage documentation
- CI/CD deployment artifacts
- Monitoring and observability configurations
- Technical documentation and runbooks
Skills and Experience
The candidate should demonstrate expertise in:
- Experience with Generative AI, Agentic AI, or LLM-based solutions.
- Proficiency in Python, including FastAPI, Pydantic and Pandas.
- Experience designing and implementing AI Harness or multi-agent frameworks.
- Hands-on experience with LangChain & LangGraph.
- Experience with Apache Iceberg, Trino, and Parquet-based lakehouse architectures.
- Experience building data ingestion, transformation, and orchestration pipelines.
- Strong knowledge of metadata management, data lineage, and data governance practices.
- Experience developing REST APIs, SDKs, and reusable engineering frameworks.
- Experience with observability, monitoring, tracing, and operational support practices.
- Strong understanding of distributed systems, event-driven architectures, and microservices patterns.
- Proven ability to design, develop, and operationalize enterprise-grade AI agents for data discovery, ingestion, transformation, optimization, governance, and observability.
- Familiar with modern data engineering technologies, including DuckDB, dbt, and related engineering tools for data transformation, modelling, and pipeline development.
We are driven by our AEIOU beliefs—Adventure, Excellence, Integrity, Ownership, and Unity—and we seek individuals who embody these values in both their professional and personal lives. We are committed to our Impact: Valuing our clients, Growing our people, and Creating our future.
Together, we make the extraordinary happen.
Learn more about us at ncs.co and visit our LinkedIn career site.
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