About the Role
You’ll design and build systems that:
+ Ingest and process high-volume, multi-source data across enterprise systems
+ Validate stateful business workflows spanning loosely coupled services
+ Reconcile data across sources with consistency and correctness guarantees
+ Build event-driven, asynchronous pipelines for real-time and batch validation
+ Integrate with complex external systems (e.g., SAP, APIs, data warehouses)
You’ll also work on:
+ Deploying LLM-powered agents into production workflows
+ Designing systems to evaluate, monitor, and improve agent behavior over time
+ Building safeguards for correctness, reliability, and failure handling
+ Ensuring non-deterministic AI outputs meet deterministic system requirements
You’ll own problems end-to-end: design → build → operate.
Tech (evolving):
+ Languages: Python, Go, Node.js
+ Data: Snowflake, Databricks, Postgres
+ Architecture: distributed systems, event-driven pipelines
+ Infra: containers + cloud platforms (Kubernetes / ECS / Cloud Run)
+ AI: LLM-based agents with evaluation, monitoring, and control systems
Why You'll Love Working at Shamrock:
+ Impactful Work: You will be solving a major pain point for the largest companies in the world.
+ Cutting-Edge Technology: Get hands-on experience with the latest in AI and LLM technology.
+ World-Class Team: Work alongside and learn from a team of seasoned entrepreneurs and industry experts.
+ Early-Stage Opportunity: Join a fast-growing startup and have a significant impact on our product and culture.
Requirements
Production builder: you’ve shipped LLM-powered features real users depend on and debugged them when they broke
LLM practitioner: you understand hallucinations, retrieval failures, context limits, and what it takes to make agents deterministic enough for enterprise use
Systems thinker: you design for latency, failure modes, retry logic, and observability before features
Enterprise-aware: data residency, compliance, audit trails, and deterministic guardrails are first-class design constraints for you
Background That Maps Well:
3+ years in AI/ML or backend engineering with strong AI exposure
Hands-on production experience with LLM APIs (Anthropic, OpenAI, Cohere)
Experience designing evaluation frameworks: automated evals, regression tests, or LLM-as-judge pipelines
Strong Python; experience with LangChain, LlamaIndex, or similar agentic frameworks
Familiarity with RAG architectures: chunking, embedding models, vector DBs, retrieval quality
About the Company
We’re building systems that continuously validate data and business processes across large enterprise environments. Enterprises run on multiple systems: ERP (e.g., SAP), APIs, internal tools, and data platforms (Databricks, Snowflake, Postgres). Inconsistencies in data - either from external vendors, internal processes, or data migrations break workflows. When AI is layered on top, those failures scale.
We build the layer that:
+ Prevents inconsistent data entry
+ Detects inconsistencies across systems
+ Validates business logic in real time
+ Enables AI-driven workflows to run safely and reliably
We’re already live at a Fortune 100 AI company and launching at Fortune 500 scale companies in healthcare and financial services.