Senior AI Engineer

5+ years of professional software engineering experience, with a proven track record of deploying and maintaining production systems.

C1 English level or higher.

Strong programming expertise in Python.

Hands-on experience building AI agents or agentic workflows using LangChain, LangGraph, Strands Agents, LlamaIndex, CrewAI, or custom frameworks.

Experience with MCP servers, tool-calling, function-calling, or similar patterns where AI agents interact with APIs, tools, or backend services.

Hands-on experience developing with LLMs using platforms such as OpenAI, Anthropic, AWS Bedrock, or similar providers.

Proven experience designing and building robust APIs and microservices using FastAPI or an equivalent framework.

Experience deploying, operating, and monitoring services within AWS cloud environments.

Experience with Docker, CI/CD pipelines, GitHub Actions, and Terraform or similar infrastructure-as-code tools.

Strong understanding of production reliability, observability, debugging, scalability, and technical debt reduction.

Skills

Python

LLM

OpenAI

Anthropic

AWS Bedrock

FastAPI

REST APIs

AWS

Design, develop, and optimize AI-driven systems, agentic workflows, and tool-using agents.

Build and maintain MCP servers or similar tool-calling layers that allow AI agents to interact safely with backend APIs, internal services, and business logic.

Develop robust AI services and APIs using Python, FastAPI, and modern backend engineering practices.

Deploy, operate, monitor, and scale AI applications in AWS environments using services such as Bedrock, Agent Core, Guardrails, Comprehend, ECS, ECR, Lambda, CloudWatch, and related infrastructure.

Implement security, validation, guardrails, and prompt-injection mitigation strategies for LLM applications handling sensitive data.

Debug, refactor, and stabilize existing production AI and LLM services to improve reliability, maintainability, latency, and performance.

Collaborate with frontend teams working with React, TypeScript, Vite, or similar technologies to integrate AI agents with user-facing product experiences.

Use CI/CD practices, GitHub Actions, Docker, Terraform, and infrastructure-as-code workflows to support reliable delivery.

Communicate technical trade-offs, project progress, risks, and architectural decisions clearly to technical and non-technical stakeholders.

LangGraph

LlamaIndex

LangChain

Docker

AWS ECS

Gunicorn

CloudWatch

Vector Databases

Semantic Search

AWS Textract

pytest

CI/CD

We provide the opportunity to participate in impactful and technically rigorous industrial data projects that drive innovation and professional growth. Our work environment emphasizes technical excellence, collaboration, and continuous innovation.

Niuro supports a 100% remote work model, allowing flexibility in work location globally. We invest in career development through ongoing training programs and leadership opportunities, ensuring continuous growth and success.

Upon successful completion of the initial contract, there is potential for long-term collaboration and stable, full-time employment, reflecting our long-term commitment to our team members.

Joining Niuro means becoming part of a global community dedicated to technological excellence and benefiting from a strong administrative support infrastructure that enables you to focus on impactful work without distraction.