AI Solutions Engineer

The AI Solutions Engineer is a key role within the AI team that partners with business teams to turn real operational challenges into practical AI-enabled solutions. This person combines strong business curiosity, consultative problem-solving, and hands-on AI capability in designing, building, testing, and improving sophisticated AI agents and workflows.

They will help teams identify where AI can create meaningful value, translate needs into clear solution designs, and build usable prototypes and production-ready solutions in collaboration with business stakeholders and technical partners.

This position is on-site in Hunt Valley, MD. Candidates must be local or willing to commute.

Key Responsibilities

Partner with the business

• Partner with business units to understand their goals, processes, pain points, and opportunities for improvement.
• Participate in discovery sessions that translate ambiguous business problems into well-defined AI solution requirements.
• Collaborate with the broader AI team to shape solution designs, provide practical feedback on feasibility and user needs, and help prioritize the AI opportunity pipeline based on business value, complexity, risk, and strategic alignment.
• Work with data, technology, security, legal, and risk partners to ensure solutions are reliable, responsible, and appropriate for the business context.

• Design, build, and iterate AI agents, copilots, automations, and workflow integrations using modern AI platforms and tools.
• Develop agent instructions, tools, knowledge sources, guardrails, and human-review workflows.
• Create prototypes that demonstrate value quickly, then help evolve successful concepts into durable solutions.

• Define success metrics and evaluation approaches before build, so each solution has a clear bar for what good looks like.
• Test AI solutions for accuracy, usefulness, safety, consistency, and user experience; continuously improve them based on feedback and performance data.
• Monitor solutions in production for adoption and accuracy drift; retire or rework anything that no longer meets its success bar.

• Explain AI capabilities, limitations, tradeoffs, and recommended practices in clear, non-technical language.
• Build adoption through training, documentation, office hours, and hands-on support for business users.
• Stay current on AI tools, agent patterns, governance practices, and emerging opportunities; bring relevant ideas back to the organization.

• 3+ years of hands-on experience building AI agents, copilots, or automations using generative AI platforms, APIs, low-code tools, or development frameworks, including work with structured and unstructured data, knowledge bases, and retrieval-augmented generation.
• 5-7+ years experience solving business problems through process improvement, consulting, business analysis, operations, or a similar role, with demonstrated ability to work with non-technical stakeholders and build trust across business functions
• Hands-on experience building AI agents, copilots, or automations using generative AI platforms, APIs, low-code tools, or development frameworks, including work with structured and unstructured data, knowledge bases, and retrieval-augmented generation.
• Experience solving business problems through process improvement, consulting, business analysis, operations, or a similar role, with demonstrated ability to work with non-technical stakeholders and build trust across business functions.
• Basic programming or scripting capability, such as Python, JavaScript, SQL, or API integration, with experience in workflow automation, systems integration, or service design.
• Experience evaluating AI systems (test cases, quality measurement, prompt iteration, monitoring) and applying responsible AI practices (privacy, security, model risk, change management).
• Strong written and verbal communication skills, including the ability to make technical topics understandable and actionable.
• Sound judgment about when AI is appropriate versus a simpler solution, and comfort experimenting, learning quickly, and moving concepts to usable solutions.

• Ability to translate business requirements into solution designs, user journeys, and measurable success criteria.
• Product management experience, including working with product roadmaps and stakeholder prioritization.
• Media or broadcast industry experience, including familiarity with newsroom, sales, or traffic operations, or systems such as WideOrbit or OSI.
• Experience with modern agent frameworks and evaluation tooling, such as LangChain, LlamaIndex, OpenAI Agents SDK, Model Context Protocol, LangSmith, or Braintrust.
• Data analysis and enterprise data platform experience, such as Snowflake, Power BI, or dbt, and SQL beyond basics.
• Prior experience on an internal AI enablement, digital transformation, or innovation team.

• Business problem framing
• Consultative stakeholder partnership
• AI agent and workflow design
• Rapid prototyping and iterative delivery
• Clear communication and enablement
• Responsible AI judgment
• Analytical thinking and prioritization
• Curiosity, adaptability, and ownership