Join #Ensiteam!

We are a company focused on custom software development and have been in the market for over 19 years. At Ensitech we are dedicated to finding highly specialized talent to work with large companies in the United States, Europe, and Canada.

We’re looking for a hands-on AI Engineer (Senior) who has already shipped LLM agents to production. You’ll build MCP servers, design RAG and memory systems, and improve agents through evaluation and real-world feedback on Amazon Bedrock and/or Microsoft Foundry. You bring 6+ years in IT, strong Python, and experience with frameworks like LangGraph or LangChain. Trading, fintech or crypto experience is a big plus.

Responsabilities

Design, build and run LLM agents in production, both client-facing and internal.
Build MCP servers on top of existing databases and production systems, and orchestrate several internal and external MCP servers under one agent.
Design memory, context management and RAG for production use.
Set up evaluation, handle edge cases and improve agents step by step after release.
Work in an architecture that combines databases, interfaces, agents and orchestrator applications.
Work on Amazon Bedrock and/or Microsoft Foundry.

Perfil del candidato

Hands-on AI engineer, Middle+ to Senior level, who has already shipped agents to production and can explain how they failed and how they were fixed.
Ambitious, learns fast, experiments with new tools and models on their own time.
Not a classic backend developer who recently added “AI” to the CV.
At least 1.5 to 2 years hands-on with LLMs and agents in production, with a background in ML/Python/DS.

Must-haves

6+ years of overall IT experience as Software Engineer, ML Engineer or AI Engineer.
Hands-on production experience with Amazon Bedrock and/or Microsoft Foundry (Azure AI Foundry, Azure OpenAI).
Built and shipped LLM agents to production, both client-facing (customer assistants, conversational AI) and internal workflow automation agents.
Strong experience with at least one agent framework: LangGraph, LangChain, LlamaIndex, Semantic Kernel, AutoGen, Strands Agents or OpenAI Agents SDK.
Deep MCP experience: building MCP servers on top of existing databases and systems, integrating external MCP servers and orchestrating several of them under one agent.
Production-grade RAG, memory and context engineering: embeddings, chunking, hybrid search, reranking, vector databases, short- and long-term agent memory.
Can name and explain agentic patterns they personally implemented (ReAct, planner-executor, reflection, router, supervisor, multi-agent, human-in-the-loop).
Experience with LLM evaluation, guardrails and monitoring of agents in production, with iterative improvement based on real usage and failure cases.
Understanding of system architecture combining databases, APIs, agents and orchestrator applications, plus practical Docker and CI/CD experience.

Nice-to-have

Trading, investing, brokerage or crypto domain knowledge combined with AI engineering (top priority for the first batch: these candidates go first).
Fintech or regulated-industry background (compliance, data protection, auditability of AI outputs).
Broader AWS or Azure cloud experience around the Bedrock/Foundry stack.
Experience with LLM evaluation and observability tools (e.g. LangSmith, Langfuse, Ragas, custom eval pipelines).
Deep practical mastery of agentic development tools for delivering full prototypes quickly (counts only on top of the must-haves, never as the main selling point).

What do we offer?

100% remote opportunity.
Competitive salary and benefits.
Custom benefit package aligned to your experience and your needs.
Working with foreign clients.