Senior AI Solutions Engineer, Business Transformation

About the Role

The Senior AI Solutions Engineer brings a track record of building and operating AI services directly, and uses that hands-on foundation to lead AI transformation across Business, Commercial, Supply Chain Management, and Staff functions. The role is part enabler and part builder: it raises what non-technical colleagues can do on their own, and personally leads the projects that go beyond their reach.

Responsibilities

• Guide business teams to the right level of AI application for their work—from everyday use of conversational AI tools, to customized assistants, to no-code and low-code development, and combinations of these.
• For each opportunity, assess what colleagues can build themselves, what enablement or training would help, and what requires a dedicated engineering project. Review resulting solutions and determine production readiness.
• Serve as project leader for a subset of the portfolio, defining the technical stack and architecture, and driving delivery hands-on for advanced builds such as LLM-based applications, RAG pipelines, agentic AI systems, and multi-agent workflows.
• Communicate effectively with local functions, IT, and leadership across diverse projects and timelines.

Qualifications

Education: Bachelor's degree or higher in Computer Science, Engineering, or a related field, or equivalent practical experience.

Experience: Minimum of 10 years in software engineering, AI service development, or technology consulting, including at least 3 years building generative AI and LLM-based services and at least 2 years leading projects as the accountable owner. Candidates are evaluated primarily on a hands-on track record of delivering services to production and breadth of exposure across organizations and customers.

Skills

• Demonstrated ability to lead a portfolio of concurrent projects—intake, prioritization, scoping, scheduling, stakeholder alignment, risk escalation, and outcome reporting.
• Practical command of AI adoption paths for non-developers—conversational AI tools, customized assistants, no-code/low-code development—and the judgment to match business needs to the right approach.
• Ability to review solutions built by non-engineers, assess production readiness, and raise them to an operable standard.
• Proficiency in defining technical stacks and architectures, and driving projects through to delivery.
• Strong proficiency in Python, with independent design, implementation, and debugging capabilities.
• SQL proficiency for data querying and transformation.
• Hands-on experience with prompt engineering, retrieval-augmented generation (RAG), agentic AI systems, and multi-agent orchestration frameworks.
• Experience deploying AI services to production in cloud (AWS or Azure) or on-premises environments, beyond PoC or prototype stages.
• Ability to build quickly with AI coding tools, validate and refactor generated code into production-ready form, and maintain full responsibility for delivered code.
• Working command of core software engineering practices: version control, containerization, CI/CD, and automated testing.
• Technical communication and enablement: Ability to explain technical judgments in non-technical terms, guide colleagues to improve their work, and provide constructive feedback with viable alternatives.
• Comfort communicating with business functions, IT, and leadership.
• Ability to quickly learn complex, multi-domain business environments (Commercial, SCM, Staff functions like Legal, HR, and Finance) and connect needs to practical technical solutions.
• Willingness to coordinate with Korea-based team members, including occasional cross-time-zone meetings.
• Professional-level English communication skills, including leading meetings and negotiating with stakeholders.

Preferred Qualifications

• Experience designing and running AI literacy or technical training programs for non-engineering audiences, and measuring adoption outcomes.
• Experience bringing solutions built by business users with AI or no-code tools into production.
• Consulting, systems integration, or agency background with exposure to diverse organizations and customer environments.
• Experience embedding observability (logging, metrics, alerting) into production services and using signals to improve system architecture.
• Experience building and deploying services under enterprise constraints (firewalls, proxies, corporate authentication) and familiarity with SSO, EAI, API Gateway, and IT infrastructure fundamentals (APIs, authentication, networking, security).
• Snowflake access control and data governance design; pipeline scheduling, dependency, and failure-handling (Snowflake Tasks, dbt, Airflow); familiarity with MLOps concepts.
• Experience reviewing and managing deliverables from external vendors or outsourced partners.
• Projects launched and operated across multiple business domains, with documented technical stack, scope of ownership, and operational outcomes.
• Mentoring junior engineers or leading technical workstreams.
• Regulated industry experience (biopharma, healthcare, or similar).

Applicants must be legally authorized to work in the United States. Visa sponsorship is not available for this position.

Pay

The anticipated salary range for this position is $135,000 to $160,000. Actual compensation may vary based on experience, qualifications, skills, and business needs.

Benefits

• 401(k) plan with company match
• Medical, dental, and vision coverage

Benefits are subject to eligibility requirements and may be modified at the Company's discretion.