AI Solutions Engineer & Business Systems Architect

Job Description:

We are seeking an AI Solutions Engineer & Business Systems Architect to design develop and deploy next-generation AI-powered business solutions that transform our operations across sales marketing communications content creation project management reporting accounting and beyond.

This role combines deep technical expertise with strong business acumen ensuring that advanced AI capabilities ranging from research prototypes to production-ready systems are translated into powerful real-world tools that create measurable business impact

You will be responsible for end-to-end ownership of the AI solution lifecycle: from research and experimentation to system architecture data engineering deployment monitoring and continuous improvement. You will build and integrate custom AI agents dashboards websites and business process automation systems while capturing and analyzing data at every stage to drive insights and innovation.

Key Responsibilities

AI Research & Prototyping

• Stay at the forefront of AI and agentic system research including prompt engineering LLM architectures and multi-agent orchestration.
  

• Rapidly prototype and test new AI-driven features workflows and systems to validate concepts before scaling.
  

• Translate emerging AI research into actionable business solutions.
  

System Design & Engineering

• Architect and develop end-to-end AI applications from data ingestion and processing pipelines to production-grade deployment.
  

• Build modular scalable AI agents for diverse business functions (sales marketing communications content generation project tracking analytics finance).
  

• Create and manage interactive dashboards admin panels and data capture systems.
  

Data Engineering & Analytics

• Integrate multiple data sources into unified AI-driven workflows.
  

• Design and maintain data pipelines feature stores and vector databases.
  

• Capture clean process and analyze data to extract actionable insights for continuous improvement.
  

MLOps & AgentOps

• Implement best practices in AI system deployment monitoring evaluation and versioning.
  

• Establish feedback loops for continuous optimization of prompts agents and workflows.
  

• Ensure observability reproducibility and maintainability of all AI-driven systems.
  

Business Impact & Strategy

• Collaborate with leadership to align AI solutions with core business objectives.
  

• Measure ROI of deployed systems and prioritize future developments for maximum business value.
  

• Educate and enable cross-functional teams to leverage AI tools effectively.
  

Requirements

Key Skills & Competencies

Core Technical Expertise

• AI & ML Research (LLM architectures agentic systems statistical analysis).
  

• Prompt Engineering & Optimization (including cross-agent dependencies and shared memory).
  

• Full-Stack Software Development (web backend APIs data storage).
  

• Data Engineering (ETL vector DBs feature stores schema design).
  

• MLOps & AgentOps (evaluation frameworks monitoring tools continuous improvement loops).
  

• Cloud Infrastructure & DevOps (CI/CD containerization orchestration).
  

Business & Analytical Skills

• Ability to translate complex AI capabilities into real-world business solutions.
  

• Strong problem-solving and systems thinking mindset.
  

• Proven track record of delivering measurable business outcomes through technology.
  

Soft Skills

• Excellent communication skills for cross-team collaboration.
  

• High adaptability in a fast-changing tech and business environment.
  

• Curiosity and continuous learning mindset.
  

Qualifications

• Bachelor s or Master s degree in Computer Science Data Science AI/ML or related field (or equivalent experience).
  

• Proven experience in AI/ML engineering software architecture and data systems.
  

• Portfolio of deployed AI applications or agent-based systems.
  

Success in This Role Looks Like:

• AI agents actively driving measurable business KPIs in sales marketing and operations.
  

• A robust scalable infrastructure for AI and data workflows.
  

• Rapid research-to-production cycle with minimal friction.
  

• Clear actionable insights generated from captured business data.