AI Engineer

Atlas Technica’s mission is to shoulder IT management, user support, and cybersecurity for our clients, who are hedge funds and other investment firms. Founded in 2016, we have grown year over year through our uncompromising focus on service.

We value ownership, execution, growth, intelligence, and camaraderie. We are looking for people who share our Core Values, thrive, and contribute to this environment while putting the customer first. At Atlas Technica, we offer a competitive salary, comprehensive benefits, and great perks to our global Team. We strive to maintain a professional yet friendly environment while promoting professional and career development for our Team Members. Join Atlas Technica now!

We are seeking an AI Engineer to join our growing AI & Advisory team in Ukraine. This is a hands-on engineering role focused on building, integrating, testing, and deploying AI-enabled applications and enterprise solutions for sophisticated client environments.

Working under the technical direction of a Principal or Senior AI Architect, the AI Engineer will translate approved architecture and security decisions into working software, integrations, deployment patterns, tests, and technical evidence. This role will build rapid proofs of concept while also helping move successful solutions toward secure, maintainable, and supportable production use.

The successful candidate will combine strong software engineering fundamentals with practical AI, Azure, integration, and security experience. This is not a research-only or prompt-engineering role; we are looking for an engineer who enjoys writing production-quality code, solving complex integration challenges, testing assumptions, and delivering reliable technical solutions.

• →Build rapid proofs of concept and production-ready components for AI-enabled research, data access, document analysis, workflow automation, reconciliation, and internal application use cases
• →Develop, review, refactor, test, and maintain application code using Python and other supported development technologies
• →Build and integrate REST APIs, MCP components, connectors, webhooks, databases, enterprise applications, and data-integration services
• →Connect AI-enabled workflows with Microsoft 365, SharePoint, Microsoft Graph, enterprise data stores, third-party platforms, and approved AI services
• →Implement retrieval and data-processing solutions using embeddings, vector or hybrid search, metadata filtering, indexing, and access-aware patterns
• →Deploy and operate applications within Microsoft Azure using approved hosting, identity, storage, database, networking, security, and deployment patterns
• →Build repeatable development and release processes using Git, CI/CD, Docker, automated testing, and infrastructure automation
• →Implement appropriate authentication, authorization, role-based access, secrets management, logging, monitoring, environment separation, and other security controls
• →Test AI solutions for reliability, security, model failure, prompt injection, inappropriate data access, unsafe tool use, dependency failure, and other production-readiness risks
• →Participate in architecture reviews, code reviews, client technical sessions, troubleshooting, production-readiness assessments, and technical handoffs
• →Maintain clear implementation documentation, diagrams, runbooks, testing evidence, and technical decisions while proactively communicating blockers, scope changes, and delivery risks
• →Contribute reusable code, deployment templates, testing approaches, connector patterns, and engineering standards to Atlas Technica’s Ukraine-based AI capability

• 5+ years of professional software engineering experience, including recent hands-on work with AI-enabled applications, cloud applications, data systems, or enterprise integrations
• Strong Python development skills with experience building APIs, services, scripts, applications, or data workflows
• Experience with at least one additional production development stack such as C#/.NET, TypeScript/Node.js, Java, or a comparable technology
• Hands-on Microsoft Azure experience across application hosting, identity, storage, databases, secrets management, logging, monitoring, and deployment
• Practical experience with LLM APIs, agentic workflows, retrieval-augmented generation (RAG), embeddings, structured outputs, prompt design, and model limitations
• Experience building or integrating APIs, connectors, MCP components, databases, data platforms, or enterprise workflow systems
• Strong understanding of authentication, authorization, role-based access control, least privilege, environment separation, and secure secrets management
• Experience with Git, CI/CD, Docker, automated testing, production troubleshooting, and modern software-development practices
• Ability to write clean, maintainable, and testable code and clearly explain technical and implementation decisions
• Strong problem-solving, ownership, documentation, and follow-through skills with the ability to work effectively in a remote and collaborative delivery environment
• English proficiency at B2 level or higher, with the ability to participate effectively in technical client discussions and produce clear written documentation

• Experience with Azure AI Foundry, Azure OpenAI, Azure AI Search, Microsoft Agent Framework, or comparable AI orchestration technologies
• Experience with Microsoft Graph, SharePoint Online, Microsoft Entra ID, Microsoft 365, Copilot Studio, or Power Platform
• Experience with technologies such as Azure Functions, Azure Container Apps, App Service, Azure SQL, PostgreSQL, Cosmos DB, Snowflake, or similar data and application platforms
• Experience developing evaluation datasets, regression tests, or other approaches for testing non-deterministic AI components
• Experience moving prototypes, internally developed applications, vendor solutions, or citizen-developed applications toward controlled production use
• Experience supporting financial services, regulated industries, enterprise clients, or other environments with strong security and compliance requirements
• Relevant Microsoft Azure, AI, software engineering, or cloud certifications
• Experience creating reusable engineering patterns, mentoring junior engineers, or contributing to engineering standards and technical knowledge sharing