Software Architect - AI Systems

WHAT YOU’LL DO:

• Design and implement robust software architectures across distributed environments.
• Lead the design and integration of GenAI components, including intelligent agents and Retrieval-Augmented Generation (RAG) pipelines.
• Collaborate with cross-functional teams to align architecture with operational and product goals.
• Apply architectural patterns such as microservices, event-driven design, and cloud-native principles.
• Create technical reference architectures, design patterns, and reusable components to guide development teams.
• Lead architecture reviews, code walkthroughs, and design sessions to promote quality and maintainability.
• Provide mentorship and guidance to engineering teams on architectural best practices and intelligent system design.
• Evaluate emerging technologies and recommend tools and frameworks that enhance system performance and reliability.
• Ensure integration and interoperability across distributed environments.
• Contribute to internal documentation and foster a culture of technical excellence.

WHAT YOU’LL NEED:

• 7+ years of software development experience, including 3+ years in an architectural or technical leadership role.
• Bachelor’s or advanced degree in Computer Science, Software Engineering, or related technical field.
• Proven experience designing and implementing AI-driven systems, especially with generative AI, LLMs, and NLP.
• Experience building AI systems with human-in-the-loop.
• Strong architectural skills across modern tech stacks such as cloud platforms, APIs, microservices, and integration patterns.
• Proficiency in modern programming languages such as Python, Java, or C#.
• Experience with cloud platforms like AWS, Azure, or GCP.
• Excellent communication skills, including the ability to explain complex concepts to technical and non-technical audiences.
• Ability to balance immediate delivery priorities with scalable system design.
• Effective communicator who can translate technical concepts to cross-functional teams.
• Ability to work within established business capability maps and operational frameworks.

PREFERRED EXPERIENCE:

• Familiarity with general data governance and compliance frameworks.
• Exposure to healthcare interoperability standards (e.g., HL7, FHIR).
• Comfortable collaborating with domain experts in specialized areas such as Life Sciences and Clinical AI.
• Life Sciences domain knowledge including clinical trials, literature review and patient cohort studies.
• Experience with containerization tools such as Docker and Kubernetes.