AI Engineer -Python, LLMs, RAG | Remote

Curvia AI; Polska; Remote; PLN 327,000 - 381,000; Part time

Job summary

Curvia AI is seeking a Forward Deployed AI Engineer to work with enterprise clients, turning complex challenges into scalable AI solutions. You will own end-to-end delivery from discovery and rapid prototyping to deployment, adoption, and continuous improvement.

You will design AI-powered applications using LLMs, agentic workflows, and RAG, integrating with enterprise environments. Close collaboration with Data and AI Engineering teams will ensure measurable business outcomes.

Qualifications

• Experience building LLM-powered apps with tool calling and structured outputs.
• Experience with LangChain, LangGraph, LlamaIndex.
• Strong understanding of RAG and vector retrieval.
• Experience designing AI agents and agentic workflows.
• Frontend experience with React/Next.js.

Responsibilities

• Own end-to-end delivery from discovery to deployment.
• Collaborate with product and engineering teams to translate business needs.
• Deliver production-grade AI applications with measurable outcomes.

Skills

LLM-powered apps

LangChain LangGraph

Python

RAG architectures

Agentic workflows

React/Next.js

Docker

CI/CD

Cloud deployments

IAM & security

Education

Degree in Computer Science or related field

Tools

LlamaIndex

LangChain

Docker

CI/CD tooling

Kubernetes

Job description

Curvia AI is a London, UK-based technology and AI solutions company that transforms complexity into opportunity through enterprise solutions, AI-powered automation, and data-driven insights. We build practical, scalable, and human-centred technology grounded in integrity, security, and responsible innovation.

About the role

We are looking for a Forward Deployed AI Engineer to join a leading digital strategy and technology consulting firm focused on AI-driven transformation and data-driven business solutions.

In this role, you will work directly with enterprise clients to understand complex business challenges and translate them into scalable, production-ready AI solutions. You will own the end-to-end delivery lifecycle, from discovery and rapid prototyping to deployment, adoption, and continuous optimisation.

You will design and implement AI-powered applications leveraging Large Language Models (LLMs), agentic workflows, Retrieval-Augmented Generation (RAG), and automation technologies. Working closely with Data Engineering and AI Engineering teams, you will integrate solutions into enterprise environments, continuously improve performance, and deliver measurable business outcomes.

You will also collaborate with technical and business stakeholders, communicate implementation strategies, and contribute reusable engineering patterns and best practices.

• Commitments Required: At least 8 hours per day and a minimum of 40 hours per week, with an overlap of 4 hours with PST.
• Employment type: Contractor assignment (no medical/paid leave)
• Contract length: 6+ months (possible extension as per performance)
• Mode of Work: Fully Remote
• Pay: US$ 60-70 per hour

Skillset

LangChain, LangGraph, Python, LLM, RAG, React/Next.JS or any similar web application technology

Special reqs

Need a Generative + Agentic AI Engineer with strong communication skills who can collaborate directly with product and engineering teams to translate complex business requirements into scalable, production-grade AI applications.

Required Skills:

• Hands-on experience developing LLM-powered applications, including tool/function calling, structured outputs, and error handling.
• Experience with LangChain, LangGraph, LlamaIndex, or comparable AI orchestration frameworks.
• Strong understanding of RAG architectures, vector retrieval, and LLM integration patterns.
• Experience designing and implementing AI agents, agentic workflows, and deterministic automation systems.
• Proficiency in React, Next.js, or similar frontend technologies for developing AI-driven interfaces.
• Experience deploying applications in cloud environments, using Docker and CI/CD pipelines.
• Understanding of enterprise integrations, IAM, secure API design, and LLM-specific security risks.
• Ability to translate business requirements into technical solutions and communicate effectively with stakeholders.
• Degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.

Bonus Skills:

• Experience with Kubernetes and container orchestration.
• Cloud platform certifications or AI-related professional certifications.
• Experience deploying AI applications in complex enterprise environments.
• Knowledge of AI application evaluation, observability, and performance optimisation.
• Experience creating reusable AI engineering components and implementation frameworks.
• Background in digital transformation, technology consulting, or client-facing engineering roles.