AI/ML Solutions Engineer
2 days ago
San Antonio
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