GBLI | Global Indemnity provides specialty property and casualty insurance for small to middle-market businesses – and we’re on a mission to be the best-in-class while achieving steady, profitable growth. Our guiding principles include the core belief that our people are number one. We also strongly emphasize a customer-centric mentality and disciplined underwriting practices. Our work environment is flexible, friendly, and collaborative, with plenty of opportunities to take charge of your career.

What GBLI offers you:

Generous paid time off (PTO)
Professional development opportunities (including a mentorship program)
Educational assistance program, which covers up to $5,250 in educational costs per year
Comprehensive health insurance plan (with vision and dental)
Paid Parental Leave
Life insurance
401(k) retirement plan with up to 6% company match and immediate vesting
Healthcare and dependent care flexible spending accounts
Short-term and long-term disability
Company-sponsored social events
Various committees to get involved in, which include our Diversity, Awareness and Inclusion Committee, and Charitable Giving Committee

The typical starting salary range for this position can vary depending on several factors such as geographic location, education, experience, and skill set. The full salary range for this position is designed to provide employees with the opportunity to progress and grow within their positions and reflects the competitive market value for these positions across the national market. GBLI, also offers a total compensation plan including bonuses for all positions.

Typical starting salary range for this position:

$135,000 to $165,000

Essential Duties & Functions

Design and build AI-powered applications and integrations across a variety of use cases
Lead implementation of small- to medium-scale AI solutions, with contribution to larger enterprise initiatives
Translate business requirements into scalable, supportable technical architectures
Design and implement data pipelines for AI/ML use cases (ingestion, transformation, and delivery)
Prepare and manage datasets for AI consumption, including cleansing, normalization, and feature engineering
Ensure data quality, lineage, and readiness for model training and inference
Apply best practices for handling sensitive data, including PII and regulated data
Evaluate and apply appropriate AI/ML (regression models, NLP, LLMs, Multi-modal models, embedding models, etc.) approaches based on use case.
Design and implement retrieval systems, including Retrieval-Augmented Generation (RAG)
Apply agentic AI patterns and architectures to enable multi-step reasoning and orchestration
Support training, fine-tuning, and optimization of models where applicable
Implement techniques such as model distillation, quantization, and performance tuning
Balance cost, performance, and accuracy in model selection and deployment
Build and integrate AI capabilities into enterprise systems, APIs, and workflows
Design scalable, secure architectures for AI services and applications
Ensure solutions are production-ready, maintainable, and aligned to enterprise standards
Engage with business stakeholders to gather and refine requirements
Clearly articulate technical concepts, trade-offs, and solution approaches
Validate requirements and translate them into actionable technical plans
Act as a bridge between business and engineering teams

Qualifications

Bachelor’s degree in a related field and 5+ years experience in software engineering, data engineering, or AI/ML engineering - or equivalent combination of education and experience.
Experience with multi-paradigm databases (vector, graph, DBMS, document, etc.)
Hands-on experience developing AI/ML solutions in production environments
Proficiency in Python and common AI/ML frameworks and tools
Excellent verbal and written communication skills, with the ability to convey technical concepts clearly and effectively
Strong critical thinking and problem-solving skills
Ability to collaborate effectively with business stakeholders, technical teams, and cross-functional partners
Self-motivated with the ability to work independently and manage competing priorities
Strong experience building data pipelines and working with structured and unstructured data
Experience with cloud platforms (e.g., Azure, AWS, or GCP), including AI and data services, Azure is preferred.
Solid understanding of data security principles and handling of sensitive data
Understanding of responsible AI, data governance, and IT governance in a regulated environment
Demonstrated ability to work independently, manage projects, and make impactful technology recommendations.

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