AI/ML Solutions Engineer

Job Summary

Seeking a talented and driven AI/ML Solutions Engineer to join a team and play a pivotal role in designing and deploying intelligent systems that enhance operational efficiency and automate workflows. This is a hands-on, high-impact position that involves collaboration across finance, operations, and leadership teams. The ideal candidate will have expertise in building machine learning pipelines and developing scalable AI-driven solutions, with a particular focus on Generative AI and LLM-based applications.

Compensation Package

• Competitive salary commensurate with experience
• Comprehensive health, dental, and vision insurance
• Generous paid time off and holidays
• Professional development opportunities
• Flexible work arrangements

Responsibilities

AI / Generative AI Development

• Design and deploy AI/ML solutions using Google Cloud tools such as Vertex AI and APIs.
• Identify and implement high-value use cases, including document processing, summarization, Q&A systems, and workflow automation.
• Develop and optimize prompt engineering, RAG pipelines, and model tuning strategies.
• Ensure AI solutions meet standards for accuracy, explainability, and compliance.
• Apply safeguards such as data redaction, access controls, and secure prompt handling.

ML Engineering & Infrastructure

• Build and maintain end-to-end ML pipelines, including data ingestion, deployment, and monitoring.
• Leverage tools such as BigQuery, Dataflow, and orchestration frameworks.
• Establish and implement MLOps best practices, including CI/CD, model versioning, and monitoring.
• Design and maintain security-focused architecture, including encryption, IAM/least-privilege access, secure APIs, and logging/auditability.

Collaboration & Stakeholder Engagement

• Partner with business teams to identify automation opportunities and translate business requirements into scalable AI/ML solutions.
• Communicate technical concepts effectively to non-technical stakeholders.
• Drive adoption of AI capabilities across the organization.

Qualifications/Requirements

Required Qualifications

• Bachelor’s degree in a related technical field.
• 3–5 years of experience in AI/ML, data science, or engineering roles.
• Hands-on experience with Google Cloud tools such as Vertex AI and BigQuery.
• Proficiency in working with LLMs, prompt engineering, and RAG frameworks.
• Strong programming skills in Python and familiarity with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Knowledge of secure development practices and cloud security fundamentals.

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