Full Stack Developer, Afficiency

• The ideal candidate will possess strong full-stack development expertise along with hands-on experience in AI technologies, agentic workflows, prompt engineering, and Large Language Model (LLM) integrations
• This role is for someone who is based in the NYC Metro Area, passionate about building real-world GenAI applications and bringing them into production, while continuously improving performance, reliability, and user outcomes
• Bachelor's Degree in Computer Science, Information Technology, Engineering, Data Science, or related discipline
• Minimum 4+ years of software engineering experience
• Minimum 2+ years developing AI-powered applications or Generative AI solutions
• Experience in Life Insurance, Financial Services, or regulated industries is highly preferred
• React.js
• JavaScript / TypeScript
• HTML5 / CSS3
• Responsive UI development
• Python
• Flask API Development
• REST APIs
• Microservices Architecture
• SQL Server, PostgreSQL, MySQL, or Oracle
• Database design and optimization
• Query performance tuning
• Prompt Engineering
• Large Language Models (LLMs)
• OpenAI GPT/Codex
• Anthropic Claude
• Google Gemini
• AI Agents and Agentic Workflows
• RAG (Retrieval Augmented Generation)
• Vector Databases
• Embeddings
• Fine-Tuning Concepts
• Model Evaluation Techniques
• Tool Calling and Function Calling
• Claude (co-work, code and design)
• Microsoft Copilot Studio
• AI Skills and Plugin Development
• Workflow Orchestration Frameworks
• Git/GitHub
• Azure DevOps
• CI/CD Pipelines

Desirable

• We are seeking a highly skilled Full Stack Developer to design, develop, and deploy AI-driven digital solutions for Life Insurance business applications
• This role will focus on building real-time AI-powered applications that enhance customer experience, underwriting, servicing, claims processing, agent productivity, knowledge management, and operational efficiency
• The successful candidate will work closely with business stakeholders, solution architects, data engineers, and digital product teams to deliver enterprise-grade AI solutions
• Design, develop, and optimize prompts for Large Language Models (LLMs) including OpenAI Codex, GPT, Claude, Gemini, and other enterprise AI platforms
• Build AI-powered workflows, copilots, virtual assistants, and intelligent agents for insurance business processes
• Develop Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge repositories and policy documentation
• Implement prompt testing, evaluation, and optimization frameworks to improve accuracy, consistency, and reliability
• Design agent-based solutions using tools, skills, plugins, function calling, workflows, and orchestration frameworks
• Create reusable prompt libraries and AI solution accelerators
• Monitor AI performance metrics and continuously improve model outcomes
• Design and develop modern web applications using React.js and related frontend technologies
• Build RESTful APIs and microservices using Python Flask
• Integrate AI services into enterprise digital applications
• Develop real-time applications supporting customer service, underwriting, policy servicing, and claims workflows
• Implement authentication, security, and scalability best practices
• Connect AI applications to enterprise systems through APIs and service layers
• Work with structured and unstructured data sources supporting AI use cases
• Participate in AI solution architecture and technology selection
• Conduct proof-of-concepts and rapid prototypes
• Collaborate with cloud, data, and application teams
• Follow DevOps, CI/CD, and Agile development practices
• Maintain documentation, technical specifications, and AI governance controls
• Success Criteria:
• Within the first 6 months, the candidate will:
• Deliver production-ready AI-powered digital applications
• Build reusable prompt engineering frameworks and AI accelerators
• Develop real-time AI agents supporting insurance operations
• Improve operational efficiency and customer experience through Generative AI solutions
• Establish best practices for AI application development, governance, and monitoring