Principal Ai Engineer (Remote in CT)

Job Description A rapidly expanding organization at the forefront of artificial intelligence, cloud technologies, and large-scale data platforms is seeking a Principal AI Engineer to join its fully remote engineering team. This opportunity is open to candidates residing in Connecticut who are excited by the challenge of building enterprise-grade AI systems used in highly complex and data-intensive environments.

As a Principal AI Engineer, you will be responsible for defining and executing the technical strategy for machine learning operations, generative AI infrastructure, and intelligent application platforms. You’ll work across cloud architecture, distributed systems, AI deployment, and platform engineering to ensure scalable, secure, and reliable AI services.

This role offers significant technical ownership for an engineer who enjoys solving difficult architecture problems, leading large initiatives, and bringing cutting-edge AI capabilities into production environments. You will partner with engineering, data, security, and product teams to create platforms that support everything from model deployment and inference to observability, governance, and optimization. Required Skills & Experience

• 10+ years of software engineering, cloud infrastructure, or platform engineering experience
• Strong track record designing and supporting large-scale distributed systems
• Experience serving as a technical lead, architect, principal engineer, or similar senior-level contributor
• Extensive experience developing and operating AI/ML platforms in production environments
• Hands-on experience deploying and supporting Large Language Models (LLMs) at scale
• Deep understanding of Retrieval-Augmented Generation (RAG), embeddings, vector search, prompt management, and AI orchestration
• Expert-level Python and TypeScript development skills
• Experience building secure, scalable APIs and backend services
• Strong knowledge of AWS cloud services and containerized workloads
• Experience with Infrastructure as Code using CloudFormation, CDK, or comparable frameworks
• Understanding of CI/CD methodologies and automation practices
• Expertise implementing observability solutions including monitoring, alerting, logging, and distributed tracing
• Experience securing multi-tenant platforms and managing sensitive data requirements
• Excellent communication skills with the ability to influence technical direction across teams

Desired Skills & Experience

• Experience with advanced LLM orchestration and agent frameworks
• Knowledge of AI evaluation pipelines, model testing strategies, and quality measurement systems
• Familiarity with AI cost optimization, GPU utilization, and inference efficiency techniques
• Experience designing agent-based applications and tool-calling workflows
• Exposure to multimodal AI solutions involving image, laboratory, or scientific datasets
• Understanding of model optimization techniques including fine-tuning, quantization, and distillation
• Experience supporting regulated environments with strict compliance requirements
• Background in life sciences, healthcare, scientific research, or laboratory technology domains

What You Will Be Doing Daily Responsibilities

• Lead architectural decisions for enterprise AI and machine learning platforms
• Design and evolve infrastructure supporting model deployment, governance, and scalability
• Build solutions for both real-time inference and large-scale batch processing workloads
• Define standards for model lifecycle management, versioning, promotion, and rollback
• Create secure frameworks for AI systems operating across multi-tenant environments
• Develop processes that ensure AI outputs meet quality, performance, and reliability objectives
• Implement monitoring and observability solutions for production AI systems
• Drive improvements in system performance, resiliency, scalability, and operational efficiency
• Collaborate with software engineers, data teams, and security stakeholders on platform initiatives
• Establish best practices for AI engineering, architecture, and deployment
• Lead technical design reviews and mentor engineers across multiple teams
• Evaluate emerging AI technologies and recommend strategic adoption opportunities
• Support infrastructure automation and cloud-native deployment processes

The Offer

• Competitive compensation package
• Fully remote position for candidates located in Connecticut -…