AI Engineer

Role Summary
You are an experienced AI Data Engineer, who will work together with AI Agent Engineers to design and create 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 to provide the data engineering know-how behind the agentic execution framework that enables multiple specialized agents to collaborate, execute tasks, maintain state, orchestrate workflows, and deliver end-to-end data engineering capabilities.
This is an exciting opportunity for someone to fuse their strong data engineering background with modern agentic AI automation.
Key Responsibilities
Setting Data Engineering Foundations
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
Supporting Specialized Agents Creation
Supporting AI Agent Engineers as SME to design and validate AI agents 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
Skills and Experience
The candidate should demonstrate expertise in:
Minimum 4++ years of relevant Data Engineering experience.
Proficiency in Python, including FastAPI, Pydantic and Pandas.
Experience with Apache Iceberg, Trino, and Parquet-based lakehouse architectures, or their equivaIents.
Experience building data ingestion, transformation, and orchestration pipelines.
Strong knowledge of metadata management, data lineage, and data governance practices.
Familiar with modern data engineering technologies, including DuckDB, dbt, and related engineering tools for data transformation, modelling, and pipeline development.
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.
Working IeveI exposure to Generative AI, Agentic AI, or LLM-based solutions.
Proven ability to design, develop, and operationalize enterprise-grade AI agents for data discovery, ingestion, transformation, optimization, governance, and observability is a strong bonus.
Experience designing and implementing AI Harness, multi-agent frameworks, LangChain and LangGraph is a bonus.
Senior engineers will be expected to have demonstrated evidence of leading technical designs, guiding junior engineering team members, working independently with clients and delivery teams, and translating AI/data requirements into scalable, secure, and deployable solutions.

Employment type
Full-time

Work arrangement
No