AI Engineer

Role Description

• Design, build, test, deploy, and operate AI agentsfor customers using a combination of low‑code and pro‑code approaches
• Develop customer‑facing AI solutions across the full Application Lifecycle Management (ALM)lifecycle, including design, development, testing, deployment, and ongoing iteration
• Build and integrate multi‑model AI agents, selecting and orchestrating models based on use case, performance, and cost considerations
• Design and implement Retrieval‑Augmented Generation (RAG)solutions, including document ingestion, vector databases, indexing strategies, and retrieval logic
• Configure and integrate MCP serversand related AI infrastructure components required for secure, scalable agent execution
• Implement secure authentication and authorizationpatterns for AI agents, including identity, permissions, and service‑to‑service access
• Collaborate with customers to understand business requirements and translate them into scalable AI agent designs
• Apply sound engineering practices including version control, environment management, testing strategies, and deployment automation
• Troubleshoot and optimize AI agents for performance, reliability, and accuracy
• Partner closely with security, data, and adoption teams to ensure AI solutions are safe, compliant, and aligned with governance requirements
• Document architectures, designs, and operational considerations as part of customer deliverables

Required Qualifications

• 5+ years of experience in software engineering, application development, or AI/automation‑focused engineering roles
• Hands‑on experience building AI agentsor AI‑powered applications using low‑code and pro‑code frameworks
• Deep understanding of AI concepts and architectures, including model inference, orchestration, and agent design patterns
• Practical experience with MCP servers, agent runtimes, or equivalent AI execution frameworks
• Strong experience designing and implementing RAG architectures, including vector databases and retrieval pipelines
• Experience working with multi‑model AI approaches, including selecting, integrating, and managing multiple models within a single solution
• Solid understanding of authentication, identity, and security controlsin application and API design
• Experience applying ALM best practicesincluding source control, CI/CD, environment promotion, and testing
• Ability to work directly with customers in solution design and delivery engagements
• Strong problem‑solving skills and comfort working in rapidly evolving technical domains

Preferred Qualifications

• Experience building AI solutions in Microsoft‑centric environments, including Copilot or Azure‑based AI services
• Familiarity with AI governance, data security, and responsible AI principles
• Experience integrating AI agents with enterprise data sources and business applications
• Background in platform engineering, cloud infrastructure, or distributed systems
• Consulting or professional services experience delivering customer‑specific solutions
• Experience collaborating with security, data, and compliance teams during solution design
• Interest in evolving toward AI architecture, solution engineering, or principal‑level technical roles