AI Engineer (LLM)

Location: Hybrid, three days per week in the office in Springfield or Boston, Massachusetts

Salary: $141,300–$185,400 annually

Company

hirify.global is an established life insurance company with an AI and Data Science team focused on enterprise AI solutions.

What you will do

• Design, build, and deliver end-to-end AI/ML solutions for complex business use cases.
• Develop applications using LLMs, deep learning, generative AI, agentic AI, and probabilistic modeling.
• Frame AI problems, define success metrics, and establish evaluation criteria with stakeholders.
• Prototype, benchmark, and quantitatively evaluate AI systems before advancing validated solutions into production.
• Build production-grade applications, APIs, dashboards, and automated pipelines while applying responsible AI and engineering standards.
• Communicate technical findings, provide peer feedback, document solutions, and share knowledge with less experienced colleagues.

Requirements

• 4+ years of experience in data science, machine learning, or AI engineering, delivering AI/ML solutions independently and at scale.
• 4+ years of experience with machine learning, statistics, NLP, LLMs, generative AI, agentic architectures, prompt engineering, and LLM evaluation.
• Experience building and deploying production AI systems, including model integration, API development, and cloud infrastructure.
• Production-quality Python programming with clean, well-tested code.
• Bachelor’s degree in computer science, statistics, applied mathematics, electrical engineering, physics, or a related quantitative field.
• Ability to work in the hybrid office arrangement in Massachusetts.

Nice to have

• Experience with Bedrock AgentCore, AWS Strands, Azure, MCP, or A2A protocols.
• Knowledge of classical ML, causal inference, optimization, Bayesian methods, SQL, database design, vector databases, or semantic search.
• Master’s degree, applied research credentials, significant open-source contributions, or demonstrated scientific rigor in industry.

Culture & Benefits

• Regular AI and Data Science team meetings and focused one-on-one meetings with a manager.
• Peer learning, candid feedback, shared technical standards, and knowledge sharing.
• Networking opportunities through multiple employee Business Resource Groups.
• Access to learning content through Degreed and other informational platforms.
• Industry-leading pay and benefits in an ethical and stable organization.