Must have

• Python

• LangGraph

• LangChain

• Gemini

• OpenAI

• Claude

• English

Nice to have

• TypeScript

• AWS

• AI agents

• Data management

• ETL

• FastAPI

• Flask

• Node.js

• Go

• PostgreSQL

• MongoDB

• Slack

• Salesforce

Requirements description

🧠 Minimum Qualifications

• 1–2+ years of hands-on experience building LLM-powered agents or complex automations
• Strong Python skills (async programming, testing, packaging)
• TypeScript experience is a plus (it’s an emerging language in our stack)
• Practical experience with LangGraph / LangChain and one or more of: n8n, AWS Bedrock, Airflow, Prefect, Temporal
• Working knowledge of Gemini, OpenAI, and Claude ecosystems (prompting, function calling, structured output)
• Solid understanding of vector stores, embeddings, RAG patterns, and data quality
• Strong software engineering foundations: Git, code reviews, CI/CD, containerization, cloud (AWS preferred)
• Familiarity with ADK (Agent Development Kit) or similar frameworks

🌟 Nice to Have

• Production experience with AI agents: evaluation frameworks, safety filters, rate-limit and cost control
• Retrieval and data management at scale: document processing, ETL, data governance
• Backend experience with FastAPI, Flask, Node.js, or Go
• Familiarity with Postgres, MongoDB, Supabase, or similar data platforms
• Workflow automation with Slack, Google Workspace, Salesforce, ServiceNow, etc.
• Observability stacks such as OpenTelemetry, Langfuse, Weights & Biases, or custom analytics

Offer description

AI Engineer / Python developer +  AWS + LLM Agents

Location: Remote-first

Employment type: B2B Contract

💡 Role Overview

We’re looking for an AI Engineer to design, implement, and maintain agentic AI systems for our clients. You’ll work across LLMs, orchestration frameworks, and data pipelines to deliver robust, observable, and secure automations.

This is not a research-only role — every project you take on will target production environments and real business use cases, with measurable impact. You’ll join a hands-on team that thrives on solving complex problems, shipping production-grade systems, and pushing the boundaries of what AI can do in real-world settings.

Your responsibilities

1. Design and implement agent architectures and multi-step orchestrations in Python
2. Build with frameworks and runtimes such as LangGraph, LangChain, n8n, AWS Bedrock, and similar tools
3. Integrate and evaluate frontier models (OpenAI GPT family, Anthropic Claude, Google Gemini)
4. Develop connectors to SaaS and enterprise systems via APIs, webhooks, queues, and events
5. Implement tools, memory, retrieval, and planning strategies for reliable agent behavior
6. Develop and maintain an internal SDK / reference agent template for reuse across projects

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