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Python Developer with AI - Remote Location

Sierra Business Solution LLCUnited States🇺🇸United StatesPosted 26 Aug 2026

Why This Role Stands Out

This remote Python Developer role offers an exciting opportunity to build and scale a cutting-edge AI platform, developing advanced skills in LLM orchestration and multi-agent systems. You'll thrive here if you're a mid-senior developer eager to contribute to impactful projects with real-time user interaction and a monthly release cadence. Apply now to join a forward-thinking team and shape the future of AI!

Quick Overview

Seniority
Mid Senior
Work mode
Remote
Location
United States
Posted
16 hours ago
FastAPIMongoDBAWSSSOGPTGenerative AIGoogle CloudKubernetesLLMPrometheusPythonRedis

Job Description

Summary

Build and scale a production multi-agent AI platform serving thousands of internal users across multiple business units. Monthly release cadence, real users, real latency, real cost.

Responsibilities

LLM-driven orchestrator that routes user intent across a portfolio of specialized agents delegation, memory, response validation, capability discovery.

Agent selection layer hybrid retrieval (vector RAG over a capability registry) plus closed-set LLM selection with JSON-schema-constrained outputs.

Multi-agent SDK gateway FastAPI service hosting many agents behind path-prefix routing, per-agent tool registries, session-scoped conversational context.

Tool-driven agents 15 30 tools per agent composed dynamically by an LLM owns tool contracts, guardrails, and evaluation.

Data API layer parameterized endpoints between agents and databases LLMs never touch DBs directly.

Partner-team onboarding versioned A2A contract, bring-your-own-agent registration, auto re-embedding.

Core AI Engineering

Production LLM systems: RAG, toolfunction-calling loops, structured outputs, hallucination guards, closed-set selection.

Multi-agent orchestration: A2A protocols, session affinity, human-in-the-loop gating, kill switches, graceful degradation.

Vector search + embeddings at scale (sub-second retrieval over thousands of docs).

Evaluation & safety: PIIPHI masking, audit trails, feedback-loop instrumentation, offline + online eval.

Platform Infrastructure

Python 3.11+, FastAPI, async IO, Pydantic.

Modern LLM stacks (Gemini, GPT, Claude) and agent frameworks (LangGraph, Agent SDKs).

Cloud (Google Cloud Platform or AWS): Kubernetes, object storage, workflow orchestration, VertexBedrock-class services.

Redis, MongoDB, OraclePostgres, SSO + RBAC.

Observability: Prometheus, structured JSON logs, per-decision audit trails, p95 latency SLOs in seconds.

Skills: Digital : PythonDigital : Machine LearningDigital : Artificial Intelligence(AI)Generative AI

Experience Required: 10 & Above

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