Lead AI & Workflow Automation Engineer

In this role, you will be directly responsible for system correctness, operational stability, and technical leadership across the following dimensions:

• Design enterprise autonomous agent pipelines with deterministic state machines and strict human-in-the-loop controls.
• Implement robust RAG pipelines with vector databases (Pinecone, Qdrant, pgvector) and hybrid semantic search.
• Develop structured evaluation frameworks benchmarking token economics, latency, and model output determinism.
• Ensure zero-data-leakage enterprise privacy protocols when interfacing with foundation model APIs.
• Build real-time monitoring and fallback systems for automated decision pipelines.

We evaluate candidates against demonstrated systems experience and sound foundational thinking:

• 6+ years in backend engineering with at least 3 years focused on production NLP/LLM orchestration.
• Proficiency with Python, TypeScript, LangChain/LlamaIndex, and distributed queue systems (Celery, BullMQ).
• Firm understanding of prompt engineering architectures, token budgets, and embeddings vectorization.
• Experience deploying models with high availability, rate limiting, and observability.

• Hands-on experience fine-tuning open models (Llama, Mistral) on domain-specific datasets.
• Familiarity with compliance standards for AI decision systems in regulated sectors.