Agentic AI Developer

Xpetize; United States; À distance; USD 120 000 - 180 000; Plein temps

Résumé du poste

Xpetize Technology Solutions (P) Ltd seeks an Agentic AI Developer who thrives at the intersection of applied LLM engineering and production software. You will design and ship AI agents and orchestration flows, reasoning loops, tool use, multi-agent coordination, memory, and governance rails that keep systems trustworthy.

You are a hands-on builder who prototypes fast, hardens what works, and owns agents from design through production, collaborating with platform, product, and design teams to

Qualifications

• 3+ years building production software with AI agents or LLM apps.
• Strong Python and TypeScript/JavaScript for full-stack work.
• Experience with at least one agent framework and one orchestration framework.
• Solid grasp of prompting, function calls, and embeddings/RAG.
• Experience with REST/async APIs, PostgreSQL, and React front-end.
• Familiarity with cloud platforms, containers, and CI/CD.

Responsabilités

• Design, build, and ship AI agents with modern frameworks.
• Architect multi-agent orchestration and stateful workflows.
• Implement tool calls, structured outputs, and external system integration.
• Build retrieval and memory layers (RAG, embeddings).
• Incorporate governance, guardrails, and audit trails.
• Set up evaluation and observability to measure reliability.
• Integrate agents into full-stack applications with platform/product/design teams.
• Optimize for cost, latency, and quality across providers.

Connaissances

Python

TypeScript/JavaScript

LLM agent development

Agent frameworks

REST APIs

Cloud platforms

Outils

OpenAI Agents SDK

Google ADK

AutoGen

CrewAI

LangChain

LangGraph

MCP

LangSmith

Langfuse

OpenTelemetry

Description du poste

We're looking for an Agentic AI Developer who lives at the intersection of applied LLM engineering and production software. You'll design and ship the AI agents and orchestration flows , reasoning loops, tool use, multi-agent coordination, memory, and the governance rails that keep them trustworthy.

You're comfortable across the stack, but your center of gravity is agent creation: turning a capability into a reliable, observable, evaluable agent. This is a hands-on builder role you'll prototype fast, harden what works, and own agents from design through production.

What You'll Do

• Design, build, and ship AI agents using modern agent frameworks — OpenAI Agents SDK, Google's Agent Development Kit (ADK), Microsoft Agent Framework / AutoGen, CrewAI, or equivalents — picking the right tool for each problem.
• Architect multi-agent orchestration and stateful workflows with LangGraph, LangChain, and similar frameworks: planning, routing, hand-offs, retries, and durable long-running execution.
• Implement robust tool / function calling, structured outputs, and externalsystem integration, including Model Context Protocol (MCP) servers and connectors.
• Build the retrieval and memory layers — RAG pipelines, embeddings, vector search, and short- and long-term agent memory.
• Bake in governance from day one: guardrails, policy enforcement, human-in-the-loop checkpoints, audit trails, and safe-failure behavior — the governed in governed orchestration.
• Stand up evaluation and observability — agent evals, LLM-as-judge, tracing, and telemetry (e.g., LangSmith, Langfuse, OpenTelemetry) — to measure and continuously improve agent reliability.
• Integrate agents into full-stack applications across APIs, services, and front-end surfaces, collaborating closely with platform, product, and design.
• Optimize for cost, latency, and quality across model providers (OpenAI, Anthropic / Claude, Google / Gemini, and open-weight models).

What You'll Bring

• 3+ years building and shipping production software, with meaningful recent hands-on experience building AI agents or LLM-powered applications.
• Should be strong in Cortex AI.
• Strong Python (the working language of agent development) and solid TypeScript / JavaScript for full-stack integration.
• Hands-on experience with at least one agent framework / SDK (OpenAI Agents SDK, Google ADK, AutoGen, CrewAI, or similar) and one orchestration framework (LangChain / LangGraph or equivalent).
• A solid grasp of LLM building blocks: prompting, function / tool calling, structured outputs, context-window management, RAG, and embeddings / vector databases.
• Full-stack fluency: REST / async APIs (FastAPI, NestJS, or similar), relational databases (PostgreSQL), and enough front-end (React) to build and integrate end-to-end.
• Familiarity with cloud (AWS, Azure, or GCP), containers (Docker), and CI/CD.
• A product mindset, strong debugging instincts, and the judgment to make nondeterministic systems behave reliably.

Nice to Have

• Experience with agent evaluation and LLM observability tooling (LangSmith, Langfuse, Arize, and similar).
• Experience with MCP, Temporal or other durable-execution engines, and eventdriven architectures.
• Exposure to enterprise / regulated environments — SSO, RBAC, data governance, and compliance.
• Fine-tuning, prompt-optimization, or model-routing experience.
• Open-source contributions in the agent / LLM ecosystem.