AI/ML Solutions Engineer

FCE is a leading Third Party Administrator (TPA) specializing in health insurance fringe benefits administration. We partner with employers, unions, and trust funds to deliver efficient, compliant, and member-centered benefits solutions.

As we invest in the next generation of our technology platform on Google Cloud, we are seeking a driven AI/ML Solutions Engineer to help harness the power of artificial intelligence—automating complex workflows and deploying intelligent tools that improve outcomes for members, clients, and internal teams. This is a hybrid position.

Position Overview

The AI/ML Solutions Engineer will be a hands-on technical contributor and subject matter expert, working closely with the CFO’s office, operations, and business stakeholders.

This is a high-impact, mid-level role for an engineer who is equally comfortable building ML pipelines and translating business needs into production-ready AI systems, with a strong focus on Generative AI and LLM-powered applications in the health insurance and benefits administration domain.

The role also requires adherence to enterprise-grade security, risk, and compliance frameworks, including SOC 1, SOC 2, and CMMC-aligned controls.

Key Responsibilities

Generative AI & LLM Implementation

• Design, build, and deploy Generative AI solutions using Google Vertex AI, Gemini APIs, and related GCP services
• Identify and prioritize high-value use cases (e.g., claims summarization, member communications, eligibility Q&A, document processing, knowledge retrieval)
• Implement prompt engineering, RAG (retrieval-augmented generation), and fine-tuning strategies to ensure accuracy in regulated environments
• Ensure solutions align with responsible AI principles, including explainability, auditability, and HIPAA compliance
• Incorporate secure prompt handling, data redaction, and model access controls to prevent data leakage and unauthorized use

ML Pipeline Development, Infrastructure & Security

• Build and maintain scalable, end-to-end ML pipelines (data ingestion → deployment → monitoring)
• Leverage GCP tools such as Vertex AI Pipelines, BigQuery ML, Dataflow, and Cloud Composer
• Establish MLOps practices (CI/CD, model versioning, monitoring, automated retraining)
• Implement security-by-design principles across ML pipelines, including:
• Data encryption (at rest and in transit)
• Identity and Access Management (IAM) with least-privilege access
• Secure API design and service authentication
• Logging, monitoring, and audit trails for all ML systems
• Align infrastructure and workflows with SOC 1 / SOC 2 controls (security, availability, confidentiality) and CMMC practices where applicable
• Partner with security and compliance teams to support audits, evidence collection, and control validation

Business Stakeholder Collaboration

• Partner with finance, operations, and leadership to identify AI opportunities that reduce administrative burden and improve outcomes
• Translate business problems into well-defined AI/ML solutions
• Communicate technical concepts clearly to non-technical stakeholders
• Serve as an internal advocate for AI/ML adoption, secure development practices, and responsible AI governance

Required Qualifications

• Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or related field
• 3–5 years of experience in AI/ML engineering, data science, or related roles
• Hands-on experience with Google Cloud Platform (GCP), including Vertex AI, BigQuery, Dataflow, and Cloud Functions
• Experience with Generative AI / LLMs, prompt engineering, and RAG pipelines
• Strong Python skills and experience with ML frameworks (TensorFlow, PyTorch, scikit-learn, XGBoost)
• Working knowledge of cloud security best practices, including IAM, encryption, secrets management, and secure SDLC

Preferred Qualifications

• Experience supporting or operating within SOC 1 and SOC 2 compliant environments
• Familiarity with CMMC (Cybersecurity Maturity Model Certification) practices and control frameworks
• Relevant certifications such as:
• Certified Information Systems Security Professional (CISSP)
• Certified Cloud Security Professional (CCSP)
• CompTIA Security
• Google Professional Cloud Security Engineer
• CMMC-related training or certification
• Experience in healthcare, insurance, TPA operations, or other regulated environments
• Familiarity with HIPAA and privacy-preserving ML techniques
• Experience with claims, eligibility, or benefits data
• Experience building internal AI tools (chatbots, document Q&A systems, automation agents)
• Strong data engineering fundamentals, including:
• SQL (PostgreSQL, MySQL)
• NoSQL (MongoDB, Cassandra)
• Data warehousing (BigQuery, Snowflake)
• Data cleaning, transformation, and feature engineering
• Real-time/stream processing systems
• Basic DevOps (Docker, Kubernetes)

Offer

• Competitive compensation commensurate with experience
• Flexible engagement structure (contract, remote/hybrid options)
• High-visibility role with direct exposure to executive leadership
• Opportunity for extension or conversion to a permanent position