AI Platform Engineer

Prophecy Technologies

Role Overview:

This role involves building and scaling a production multi-agent AI platform designed to serve thousands of internal users across various business units. The platform will operate with a monthly release cadence, addressing real-world challenges related to user experience, latency, and cost efficiency.

Key Responsibilities:

Develop an LLM-driven orchestrator for routing user intent across a portfolio of specialized agents, managing delegation, memory, response validation, and capability discovery.
Implement an agent selection layer utilizing hybrid retrieval (vector RAG over a capability registry) and closed-set LLM selection with JSON-schema-constrained outputs.
Build a multi-agent SDK/gateway using FastAPI, hosting multiple agents behind path-prefix routing, managing per-agent tool registries, and session-scoped conversational context.
Create tool-driven agents with 15-30 dynamically composed tools by an LLM, ensuring tool contracts, guardrails, and evaluation.
Design and implement a data API layer with parameterized endpoints between agents and databases, ensuring LLMs do not directly interact with databases.
Facilitate partner-team onboarding, including versioned A2A contracts, bring-your-own-agent registration, and auto re-embedding.

Required Skills:

Proficiency in production LLM systems, including RAG, tool/function-calling loops, structured outputs, hallucination guards, and closed-set selection.
Experience with multi-agent orchestration, A2A protocols, session affinity, human-in-the-loop gating, kill switches, and graceful degradation.
Expertise in vector search and embeddings at scale, achieving sub-second retrieval over thousands of documents.
Knowledge of evaluation & safety practices: PII/PHI masking, audit trails, feedback-loop instrumentation, and offline + online evaluation.
Strong programming skills in Python 3.11+, FastAPI, async I/O, and Pydantic.
Familiarity with modern LLM stacks such as Gemini, GPT, Claude, and agent frameworks like LangGraph and other Agent SDKs.
Cloud platform experience (GCP or AWS), including Kubernetes, object storage, workflow orchestration, and Vertex/Bedrock-class services.
Database and caching experience with Redis, MongoDB, Oracle/Postgres, and knowledge of SSO + RBAC.
Understanding of observability tools and practices: Prometheus, structured JSON logs, per-decision audit trails, and p95 latency SLOs.
Skills in Machine Learning, Artificial Intelligence (AI), and Generative AI.

Qualifications:

4-6 years of experience in a relevant engineering role.

Apply

Vacancy posted 4 days ago

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