Software Architect

Salary Range: 200000 to 250000 (Currency: USD) (Pay period: per-year-salary)

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.