Lead Software Engineer Emerging Tech and AI Cloud Solutions

Education Requirements: Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Technology, or related field. Preferred Education: Master's degree.

Preferred Certifications: Cloud certification, AI/ML certification, Software Architecture certification. Required Skills for the Lead Software Engineer: 8+ years of experience, Decision Making and Critical Thinking, Software Development, Software Development Life Cycle, Software Integration Engineering, Software Product Design/Architecture, Software Product Technical Knowledge, Software Product Testing, Progressive professional experience in software engineering, Demonstrated ability to lead technical work across the full software development lifecycle, Strong proficiency in one or more modern programming languages such as Python, Java, JavaScript/TypeScript, C#, Go, or similar languages, Experience designing scalable, secure, observable, and maintainable software using modern architecture patterns, APIs, automated testing, CI/CD, and DevOps 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.

Preferred Skills: Experience building or integrating AI, machine learning, generative AI, large language model, agentic, retrieval-augmented generation, vector database, or prompt-based solutions, Experience taking emerging technology concepts from proof of concept through pilot, production hardening, governance review, adoption, and operational support, Familiarity with responsible AI practices, model evaluation, guardrails, data privacy, cybersecurity, compliance, and enterprise risk management considerations, Experience with modern cloud services, serverless architectures, Kubernetes, microservices, event-driven architecture, API management, observability platforms, and infrastructure-as-code, Experience partnering with product, design, data, security, architecture, and business teams to identify high-impact use cases and deliver measurable business outcomes, Proven ability to mentor engineers, influence technical direction without direct authority, and establish reusable engineering standards, patterns, frameworks, or accelerators.

Lead Software Engineer Overview: The Lead Software Engineer in the Emerging Technology group is a hands-on technical leader responsible for designing, building, piloting, and scaling next-generation software solutions that apply emerging technologies to high-value business problems. This role combines deep software engineering expertise with practical innovation, helping translate exploratory concepts into secure, reliable, maintainable, and production-ready capabilities.

Responsibilities: 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 a culture of experimentation, learning, engineering excellence, and responsible technology adoption, Collaborate with product managers, architects, data scientists, cybersecurity, infrastructure, UX, and business stakeholders to deliver solutions aligned to organizational goals and risk expectations, Define and implement technical evaluation methods, including proof-of-concept success criteria, model or system performance measures, quality gates, automated testing, monitoring, and production readiness reviews, Identify technical risks, dependencies, integration needs, security considerations, and operational constraints early in the solution lifecycle and recommend practical mitigation strategies.