Python Developer with AWS and AI
4 dni temu
Location: Remote-first
Employment type: B2B Contract
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.
What You'll DoDesign and implement agent architectures and multi-step orchestrations in Python
Build with frameworks and runtimes such as LangGraph, LangChain, n8n, AWS Bedrock, and similar tools
Integrate and evaluate frontier models (OpenAI GPT family, Anthropic Claude, Google Gemini)
Develop connectors to SaaS and enterprise systems via APIs, webhooks, queues, and events
Implement tools, memory, retrieval, and planning strategies for reliable agent behavior
Develop and maintain an internal SDK / reference agent template for reuse across projects
Productionize prototypes: CI/CD, packaging, containerization, and cloud deployment (AWS preferred)
Add observability to agents: logging, tracing, evaluation, offline analysis, and guardrails
Collaborate with clients to gather requirements, run experiments, and iterate quickly
Facilitate design thinking workshops to map business needs into agent capabilities and success metrics
Apply security, privacy, and safety best practices for data and model usage
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
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, , 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
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