Artificial Intelligence Engineer

About the role

We are looking for an experienced AI Software Engineer who enjoys solving complex business problems by designing and delivering intelligent applications that operate in production environments. This role is ideal for someone who combines strong software engineering expertise with practical experience building AI-powered solutions. You'll take ownership of projects from concept through deployment, partnering with technical teams and business stakeholders to create scalable, reliable systems that generate measurable value.

This is a senior individual contributor position reporting to the Engineering leadership team. Success in this role requires technical independence, sound architectural judgment, and the ability to move ambiguous ideas into production-ready solutions with minimal direction.

Key Responsibilities

Lead the complete software development lifecycle for AI initiatives, including requirements discovery, architecture, development, testing, deployment, monitoring, and ongoing enhancement.

Collaborate with business partners to understand operational workflows, identify opportunities for automation, and implement AI-driven solutions that improve efficiency and productivity.

Design and develop intelligent agent-based applications utilizing modern orchestration frameworks, memory management, retrieval mechanisms, tool integration, and governance controls.

Build and maintain production-quality applications using technologies such as C#/.NET, Python, and modern JavaScript/TypeScript frameworks including React.

Develop secure APIs, backend services, and user-facing interfaces that enable reliable adoption of AI capabilities across the organization.

Deploy and support AI workloads within Microsoft Azure, leveraging Azure AI services and related cloud technologies to manage model selection, evaluation, deployment, and lifecycle management.

Establish testing strategies, evaluation frameworks, and performance metrics that improve model quality, reduce errors, and ensure dependable production performance.

Troubleshoot application issues, optimize system performance, and resolve production incidents involving AI services and supporting infrastructure.

Partner with security, compliance, and infrastructure teams to ensure solutions meet organizational standards for governance, data protection, and access control.

Produce technical documentation covering architecture, implementation decisions, operational procedures, and support processes.

Promote engineering best practices through code reviews, software design standards, automated testing, and disciplined development processes.

Qualifications

Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent professional experience.

Approximately 3+ years of experience designing, developing, and deploying production software applications.

Strong foundation in software engineering principles, object-oriented programming, system architecture, algorithms, and application testing.

Professional development experience with Python, C#, .NET, and modern front-end technologies such as TypeScript and React.

Experience operating production applications, including CI/CD pipelines, monitoring, logging, observability, and incident management.

Hands-on experience implementing AI or large language model solutions in enterprise environments.

Familiarity with Azure AI services is preferred; experience with comparable cloud AI platforms such as AWS or Google Cloud is also valuable.

Ability to translate loosely defined business objectives into practical technical solutions.

Strong organizational skills with the ability to manage multiple priorities while maintaining high-quality delivery.

Excellent written and verbal communication skills, with the ability to work effectively across technical and non-technical teams.

Preferred Experience

Building retrieval-augmented generation (RAG) solutions, including document ingestion, indexing strategies, vector search, and retrieval optimization.

Developing AI applications that integrate with enterprise platforms through APIs, messaging services, or workflow automation tools.

Experience working within structured software development methodologies in large enterprise environments.

Knowledge of security, governance, and compliance practices involving sensitive or regulated data.

Experience creating automated evaluation pipelines, regression testing, and benchmarking processes for AI models, prompts, and intelligent agents.

Demonstrated ability to independently deliver complex technical solutions in fast-paced, innovation-focused organizations.