Senior AI Developer

Stellix helps organizations in the life sciences and other critical industries connect strategy, systems, and teams so they can turn digital and AI investments into measurable operational results. Join our team as we design, implement, and govern the adaptive operating models that produce outcomes that matter to our clients and the communities they serve.

The Senior AI Developer is responsible for designing, developing, integrating, deploying, and supporting artificial intelligence solutions across a broad range of business, engineering, and customer use cases.

The role supports the full AI solution lifecycle, from research and prototyping through production deployment, optimization, and scale. The individual will work with machine learning, generative AI, intelligent automation, agentic AI, and emerging technologies to deliver secure, reliable, maintainable, and reusable enterprise AI solutions.

This role is not limited to a specific technology, platform, or use case and requires the ability to adapt as AI technologies, customer needs, and business requirements evolve.

• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Computer Engineering, Software Engineering, or a related technical field.
• Strong proficiency in Python with a solid foundation in software engineering and application development.
• Strong understanding of artificial intelligence and machine learning, including generative AI and emerging AI technologies.
• Experience with or knowledge of commonly used AI/ML libraries and frameworks.
• Understanding of AI agents, intelligent automation, information retrieval, embeddings, semantic search, and vector-based data retrieval.
• Experience developing and integrating APIs, backend services, databases, data pipelines, and AI/ML capabilities into applications.
• Working knowledge of SQL and relational databases, such as SQL Server, PostgreSQL, or equivalent technologies.
• Proficiency with Git and source control practices in a collaborative software development environment.
• Experience with or exposure to additional enterprise development technologies such as C#/.NET.
• Familiarity with containerization technologies such as Docker, application deployment, and environment configuration and troubleshooting.
• Understanding of cloud, on-premises, and hybrid environments and considerations for deploying and operating AI solutions.
• Understanding of production software and AI considerations, including performance, scalability, reliability, monitoring, security, testing, and maintainability.

• Design, develop, test, deploy, and support AI-enabled applications and services.
• Translate business and customer needs into practical and scalable AI solutions.
• Integrate AI capabilities with enterprise applications, data, services, and business workflows.
• Prototype and evaluate emerging AI technologies and transition successful concepts into production solutions.
• Develop reusable AI capabilities, components, and technical patterns that can support multiple applications, business functions, and customer use cases.
• Evaluate and continuously improve AI solution quality, performance, reliability, and scalability.
• Contribute to AI architecture, technical documentation, development standards, and engineering best practices.

• Strong analytical thinking, problem-solving, and problem-decomposition skills.
• Ability to independently research and work through unfamiliar technical challenges.
• Curiosity and willingness to continuously learn and adapt as AI technologies evolve.
• Ability to balance experimentation and innovation with established project objectives, priorities, scope, and timelines.
• Sound judgment when evaluating new technologies and alternative approaches without unnecessarily changing project direction.
• Strong attention to quality, reliability, maintainability, security, and technical detail.
• Effective communication and collaboration with technical teams, subject matter experts, business stakeholders, and customers.
• Demonstrates ownership, accountability, effective time management, and prioritization.
• Ability to adapt to different business domains, customer requirements, and technical environments.

• Delivers AI-enabled applications and services on time, within scope, and aligned with business and customer requirements.
• Transitions successful AI prototypes and emerging technology evaluations into secure, maintainable,…