Senior AI Engineer

About the Role:

In this senior-level role, you will lead the architecture and evolution of AI-powered systems that transform probabilistic model outputs into reliable, production-grade product capabilities. You will design and ship systems around agents, retrieval pipelines, orchestration layers, and evaluation frameworks, while defining the architectural standards that ensure AI-driven features operate safely and at scale across our platform.

This is not a feature-delivery role - it is a systems-definition role. Your decisions will shape how AI capabilities are built, evaluated, and deployed across the organization.

About the Team:

Our AI Foundations team is building the foundation for how AI will power the next generation of products at Employ. This is a high-ownership, high-autonomy team responsible for turning rapidly evolving model capabilities into reliable, customer-facing systems.

What You'll Do:

Architect & Ship AI-Native Systems

• Lead the architecture and delivery of end-to-end AI-powered systems, including agents, RAG pipelines, orchestration layers, and reasoning workflows.

• Translate product vision into scalable technical systems.

• Define contracts, state management strategies, and guardrails for AI-driven workflows.

• Own and evolve API contracts that AI systems interact with, ensuring reliability, idempotency, authentication safety, and rate limiting.

Engineer Reliability at Scale

• Design schema enforcement and validation layers for AI-generated outputs.

• Implement retries, fallback strategies, and failure-mode containment.

• Establish evaluation frameworks for benchmarking, regression testing, and drift detection.

• Create observability standards for AI systems, including structured logging, telemetry, tracing, and performance monitoring.

• Productionize experimental AI capabilities into scalable, secure services.

Set Direction & Elevate the Organization

• Establish architectural patterns and standards adopted across teams.

• Mentor engineers in AI-native and spec-driven development practices.

• Influence engineering culture through clarity, urgency, and execution.

• Decompose high-level business outcomes into executable technical systems.

What You Bring:

You have mastered the fundamentals of software engineering and operate at a higher level of abstraction. You are not simply accepting AI-generated code - you review, restructure, and integrate it into cohesive, production-grade systems.

• 4+ years building AI-augmented product capabilities (LLMs, RAG systems, agents, orchestration frameworks).
• Event-Driven & Asynchronous Systems : Experience designing decoupled systems using queues such as Kafka, SQS, or BullMQ, and implementing asynchronous workflows that prevent blocking operations in user-facing systems.
• State Management Strategy : Experience persisting state across sessions, managing context windows efficiently, and handling concurrency and race conditions when multiple agents interact with shared data.
• Structured Data Enforcement : Experience enforcing structured outputs using schema validation tools such as Pydantic, Zod, or JSON Schema to ensure AI-generated outputs are reliable and machine-readable.
• API Design & Integration : Strong understanding of REST, GraphQL, or RPC interface design, along with authentication, rate limiting, and idempotent API patterns.

Tech Stack & Hard Skills:

Languages: Python, including asyncio, decorators, and the modern Python ecosystem. TypeScript / Node for integration and application-layer logic

AI Stack: Orchestration frameworks such as LangChain, LangGraph, or custom agent loops. Retrieval-Augmented Generation (RAG) systems. Hybrid search, re-ranking, and chunking strategies. Vector databases such as Pinecone, pgvector, or Weaviate

Database & Infrastructure: Advanced SQL skills including query optimization and indexing strategies. Containerization using Docker, Kubernetes or similar orchestration platforms. Experience running isolated environments for code execution