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 OverviewThe 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 ResponsibilitiesGenerative AI & LLM ImplementationDesign, build, and deploy Generative AI solutions using Google Vertex AI, Gemini APIs, and related GCP servicesIdentify 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 environmentsEnsure solutions align with responsible AI principles, including explainability, auditability, and HIPAA complianceIncorporate secure prompt handling, data redaction, and model access controls to prevent data leakage and unauthorized useML Pipeline Development, Infrastructure & SecurityBuild 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 ComposerEstablish 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 accessSecure API design and service authenticationLogging, monitoring, and audit trails for all ML systemsAlign infrastructure and workflows with SOC 1 / SOC 2 controls (security, availability, confidentiality) and CMMC practices where applicablePartner with security and compliance teams to support audits, evidence collection, and control validationBusiness Stakeholder CollaborationPartner with finance, operations, and leadership to identify AI opportunities that reduce administrative burden and improve outcomesTranslate business problems into well-defined AI/ML solutionsCommunicate technical concepts clearly to non-technical stakeholdersServe as an internal advocate for AI/ML adoption, secure development practices, and responsible AI governanceRequired QualificationsBachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or related field3–5 years of experience in AI/ML engineering, data science, or related rolesHands-on experience with Google Cloud Platform (GCP), including Vertex AI, BigQuery, Dataflow, and Cloud FunctionsExperience with Generative AI / LLMs, prompt engineering, and RAG pipelinesStrong 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 SDLCPreferred QualificationsExperience supporting or operating within SOC 1 and SOC 2 compliant environmentsFamiliarity with CMMC (Cybersecurity Maturity Model Certification) practices and control frameworksRelevant certifications such as:Certified Information Systems Security Professional (CISSP)Certified Cloud Security Professional (CCSP)CompTIA Security+Google Professional Cloud Security EngineerCMMC-related training or certificationExperience in healthcare, insurance, TPA operations, or other regulated environmentsFamiliarity with HIPAA and privacy-preserving ML techniquesExperience with claims, eligibility, or benefits dataExperience 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 engineeringReal-time/stream processing systemsBasic DevOps (Docker, Kubernetes)OfferCompetitive compensation commensurate with experienceFlexible engagement structure (contract, remote/hybrid options)High-visibility role with direct exposure to executive leadershipOpportunity for extension or conversion to a permanent position