Software AI Engineer

Svitla Systems Inc. is looking for a Software AI Engineer for a full-time position (40 hours per week) in Argentina. Our client is one of the world’s largest and fastest-growing job sites.

REQUIREMENTS

• 4+ years of experience in software engineering, backend engineering, or applied AI engineering.
• Strong programming skills in Java and/or Python.
• Hands-on experience building AI-powered applications or integrating LLM capabilities into production systems.
• Experience designing or building AI agents, multi-step orchestration workflows, or tool-using automation systems.
• Experience with MCP or similar integration patterns for connecting AI systems to external tools, APIs, or enterprise platforms.
• Strong understanding of system design, APIs, distributed systems, and production software engineering fundamentals.
• Familiarity with prompt design, context management, evaluation approaches, and reliability patterns for agent-based systems.
• Proven ability to work effectively in fast-paced delivery environments.
• Delivery-oriented and comfortable operating across development, experimentation, and production support responsibilities.
• Effective at collaborating with cross-functional teams under tight timelines.
• Strong ownership mindset with practical problem-solving skills.

NICE TO HAVE

• Experience with multi-agent systems, retrieval-augmented generation, semantic search, or vector-based architectures.
• Familiarity with cloud-native infrastructure, monitoring, and observability for AI services.
• Experience with model evaluation, guardrails, safety patterns, and prompt/version lifecycle management.
• Experience integrating AI solutions with enterprise platforms such as Salesforce, Jira, Slack, or internal developer tools.
• Background in workflow automation, event-driven systems, or backend platforms that support AI-enabled products.

RESPONSIBILITIES

• Design, build, and enhance AI-powered applications and backend services for internal or customer-facing use cases.
• Build and maintain AI agents and agentic workflows that can reason, orchestrate tasks, and integrate with enterprise tools and services.
• Develop MCP-based integrations and tool interfaces that enable AI systems to interact securely with external platforms, APIs, and business systems.
• Implement prompt orchestration, context handling, tool calling, memory patterns, and evaluation workflows for reliable agent behavior.
• Collaborate with engineering, product, and architecture teams to define scalable patterns for AI agent development and deployment.
• Integrate LLM capabilities into software systems while balancing performance, reliability, cost, and safety.
• Investigate system issues, improve quality and observability, and optimize AI workflow efficiency in production environments.
• Participate in code reviews, release support, experimentation, and production incident resolution.
• Create technical documentation and contribute to best practices for AI engineering, agent development, and MCP adoption.