Lead Software Engineer

• Lead the architecture, design, development, and testing of modern software solutions, prototypes, pilots, and reusable platform capabilities
• Evaluate, prototype, and apply emerging technologies such as generative AI, agentic workflows, retrieval-augmented generation, cloud-native services, APIs, automation, and data-driven application patterns
• Translate business opportunities, product goals, and technical requirements into scalable software designs, solution patterns, technical roadmaps, and implementation plans
• Mentor engineers, provide technical direction, facilitate design reviews, and promote experimentation, learning, engineering excellence, and responsible technology adoption
• Collaborate with product managers, architects, data scientists, cybersecurity, infrastructure, UX, and business stakeholders
• Define technical evaluation methods, proof-of-concept success criteria, performance measures, quality gates, automated testing, monitoring, and production readiness reviews
• Identify technical risks, dependencies, integration needs, security considerations, and operational constraints, and recommend mitigation strategies

• Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, Information Technology, or a related technical discipline; equivalent practical experience may be considered
• Progressive professional experience in software engineering, including hands-on development of complex applications, distributed systems, APIs, platforms, or cloud-native services
• Ability to lead technical work across the full software development lifecycle, including requirements analysis, architecture, design, coding, testing, and deployment
• Strong proficiency in one or more modern programming languages such as Python, Java, JavaScript/Type Script, C#, Go, or similar languages
• Experience designing scalable, secure, observable, and maintainable software using modern architecture patterns, APIs, automated testing, CI/CD, and Dev Ops practices
• Working knowledge of cloud platforms, containerization, infrastructure automation, integration patterns, and production support practices
• Ability to communicate complex technical topics clearly to engineering, product, architecture, security, and business stakeholders
• Demonstrated analytical, problem-solving, and decision-making skills in ambiguous or rapidly evolving technical environments
• No visa sponsorship available
• Must successfully complete a drug screen
• Preferred:
  Experience with AI, machine learning, generative AI, large language models, agentic solutions, retrieval-augmented generation, vector databases, or prompt-based solutions
• Preferred:
  Experience taking emerging technology concepts from proof of concept through pilot, production hardening, governance review, adoption, and operational support
• Preferred:
  Familiarity with responsible AI practices, model evaluation, guardrails, data privacy, cybersecurity, compliance, and enterprise risk management
• Preferred:
  Experience with modern cloud services, serverless architectures, Kubernetes, microservices, event-driven architecture, API management, observability platforms, and infrastructure-as-code
• Preferred:
  Advanced degree, cloud certification, AI/ML certification, software architecture certification, or contributions to technical communities, open-source projects, patents, publications, or internal innovation initiatives

Demonstrates expertise in software architecture, design, and development, with a strong focus on scalable and secure solutions using modern programming languages and cloud-native services. Proven ability to lead technical teams, mentor engineers, and communicate complex technical concepts effectively across various stakeholders.

• Software Architecture
• Cloud-Native Services
• Modern Programming Languages
• Automated Testing
• Technical Leadership

• Software Development Lifecycle
• APIs
• Distributed Systems
• CI/CD
• Dev Ops Practices
• Python
• Java
• JavaScript/Type Script
• C#
• Go

• Analytical Skills
• Problem-Solving
• Decision-Making
• Communication Skills

• Cloud Certification
• AI/ML Certification
• Software Architecture Certification

• Generative AI
• Machine Learning
• Data Privacy
• Cybersecurity
• Compliance
• Enterprise Risk Management

• Kubernetes
• Microservices
• Event-Driven Architecture
• Observability Platforms
• Infrastructure-as-Code