AI Engineer

COMPANY 
Atlas Technica is a fast-growing US-based MSP working with some of the world’s largest hedge funds and investment firms.
Founded in New York in 2016, the company has grown to 200+ engineers across 10+ countries (US, UK, Ukraine, Hong Kong, Singapore).
Atlas Technica combines product-level engineering standards with a strong service culture, partnering directly with top-tier investment firms on their digital transformation and automation initiatives.

We are seeking an AI Engineering professional to join our DevOps team. The goal of this role is to design and deploy intelligent chatbots using Azure Bot Framework, OpenAI, and Cognitive Services. Build data pipelines and fine-tune NLP models with Azure ML. Integrate AI with enterprise systems via RESTful APIs, ensuring compliance with security and privacy standards. Stay current with LLM advancements, collaborate across teams, and mentor junior engineers. You’ll join a technically mature environment with strong engineering leadership and the opportunity to own and shape the company’s first in-house AI direction.

Location/Type: Remote
Hours: 10 AM-7 PM UA

Hiring process: 2-3 interviews
 

Responsibilities

AI Agent & Chatbot Development
• Design, build, and deploy intelligent conversational agents using Azure Bot Framework, Azure OpenAI, and Cognitive Services.
• Develop prompt strategies and manage datasets to support context-aware, multi-turn dialogue and accurate responses.
• Conduct rapid prototyping to validate technical feasibility and demonstrate the business value of AI-driven solutions.

Data & Model Engineering
• Build and maintain robust data pipelines to support training and inference workflows.
• Configure, train, and fine-tune machine learning models using Azure Machine Learning, with a focus on NLP and LLMs.
• Evaluate and optimise AI system performance for accuracy, scalability, latency, and cost-efficiency.

System Integration & Architecture
• Architect and implement integration between AI and enterprise systems (e.g., ConnectWise Manage, Confluence, etc) using RESTful APIs.

Security, Compliance & Governance
• Ensure AI systems comply with data privacy regulations (e.g., GDPR) and enterprise-grade security standards.
• Implement access controls, data encryption, and audit logging for sensitive AI workflows.

Research & Innovation
• Stay current with evolving LLM technologies, frameworks and methodologies.
• Evaluate emerging tools and techniques to improve solution quality and delivery speed continuously.

Collaboration & Leadership
• Work closely with cross-functional teams to interpret business requirements and recommend LLM-driven solutions.
• Contribute to technical and architectural decisions, ensuring alignment with strategic goals.
• Mentor junior engineers and support knowledge sharing across the team.

Operational Excellence
• Take ownership of production releases, incident resolution, and bug fixes.
• Create and maintain technical documentation for AI systems, models, and integration workflows.

Requirements:

• English level – B2 or higher
• 5+ years of experience in AI engineering and ASP.NET software development (Core/WebAPI, C#, React/React.js), with a focus on Azure-based solutions.
• Experience building intelligent chatbots and autonomous agents (Agentic AI) that perform real actions, plan, reason, and act with minimal human input; familiar with multi-agent orchestration and agent memory.
• Advanced expertise in machine learning, deep learning, and NLP, including pipelines, model fine-tuning, embeddings, and transformer-based architectures.
• Strong understanding of large language models (LLMs), their limitations, and modern capabilities (e.g., GPT, Claude, Gemini), as well as practical experience with Retrieval-Augmented Generation (RAG) and optimising retrieval pipelines.
• Hands-on experience with Azure AI services (Azure Machine Learning, Cognitive Services, Bot Framework) and knowledge of MCP or similar protocols for secure, scalable integration between AI agents and enterprise systems.
• Familiarity with deploying, monitoring, and maintaining ML models in production environments.
• Ability to write clean, maintainable, and testable code following SOLID principles and Clean Architecture patterns.

Desirable Qualities

• Understanding of retrieval systems (keyword search, vector search, embeddings) and ranking algorithms.
• Familiarity with CI/CD pipelines and DevOps practices.
• Experience with Azure Cosmos DB.
• AI-102
• Prior experience integrating AI agents with enterprise platforms like ConnectWise Manage, Confluence, SPO, etc.