Artificial Intelligence Engineer Position Available In Wake, North Carolina

Role:

Senior AI Engineer Location:

Cary, NC (day1 onsite)

Full Time Tech Stack Development & Delivery Methods:

Agile (Scaled Agile Framework)

DevOps and CI/CD:

Containers (Azure Kubernetes) CI/CD (Azure DevOps, Git, SonarQube) Scheduling Tools (Azure Scheduler)

Development Frameworks and Languages:

AI:

Machine learning, deep learning, neural networks,

NLP, LLM’s App:

Microservices (Java, Spring boot) UI & Web (ReactJS, HTML, Javascript)

Data Management:

Database (SQL Server, Cosmos DB) APIs (Kong, APIC, APIM)

Development Tools & Platforms:

IDE (GitHub Copilot, VSCODE, IntelliJ) Cloud Platform (Microsoft Azure)

Security and Monitoring:

Secure Coding (Veracode) Authentication/Authorization (CA SiteMinder, MS Entra, PingOne) Log & Monitoring (Azure AppInsights, Elastic)

Skill & Job Description:

The AI Engineer will be responsible for design development of innovative AI solutions and contributing to the strategic vision of our organization.

Key Responsibilities:

Define and implement GenAI building standards to ensure consistency, quality, and scalability across projects Stay abreast of advancements in GenAI and agentic systems, translating emerging trends into actionable opportunities Hands-on engineer in technical design and development of AI applications using existing and/or emerging technology. Work closely with product managers, data scientists and other stakeholders to translate business requirements into scalable and efficient AI solutions. Collaborate with cross-functional teams to execute the AI technology roadmap, aligning with business objectives and industry trends. Stay abreast of the latest advancements in AI technologies, guiding the team in adopting best practices and cutting-edge methodologies. Responsible for development of AI specific software/platform components. Investigate and resolve production management incidents, problems, and service requests. Implementation of AI technology best practices, architecture and technology stack including adoption of cloud, Data, and other relevant emerging technology that is fit-for-purpose. Ways of Working – Adoption of the Agile ways of working in the software delivery lifecycle and continuous learning of new methods and technology

Experience:

5+ years in development using multiple technology stack capabilities (Front/Back End, API, Database Mgmt., Hosting technologies etc. to drive digital transformation in financial services or technology domain Proven expertise in developing and delivering GenAI applications, including agentic systems Strong understanding of modern AI/ML frameworks, cloud platforms (e.g., AWS, Azure, GCP), and data engineering practices. Experience with LLMs, transformers, and understanding of agentic systems, current limitations and opportunities. Experience in implementing Enterprise AI solutions leveraging AIML models. Expertise in machine learning, deep learning, natural language processing, and other AI-related technologies. Proficiency in programming languages such as Python and proficiency with AI frameworks (e.g., TensorFlow, PyTorch) Strong grounding on data engineering and design to support AI workloads. Hands on experience on Azure AI offerings will be an added advantage. Strong analytical and problem-solving skills with a focus on delivering practical, scalable solutions. Hands-on experience in developing and implementing applications using modern technology stack and patterns including cloud native patterns, public cloud (e.g. Microsoft Azure), AI/Big Data, API and web apps Proficiency in software development lifecycle including CI/CD, test driven development, domain driven design and Agile ways of working (including shift-left) Regards, Shweta Sharma shweta.sharma@msrtechnologies.com