AI Engineer

• Design, develop, and deploy AI and Generative AI applications using cloud-native services and modern software engineering practices
• Build and maintain AI-powered solutions using AWS Bedrock, GCP Vertex AI, large language models, and machine learning frameworks
• Develop Retrieval-Augmented Generation systems, including document ingestion, vector search, embeddings, and retrieval pipelines
• Create, test, and optimize prompts, workflows, and agentic AI solutions using Bedrock Agents, Vertex AI Agent Builder, LangChain, LangGraph, LlamaIndex, or similar frameworks
• Develop APIs, microservices, and event-driven integrations for scalable and secure AI capabilities
• Collaborate with product owners, engineers, data teams, security teams, and business stakeholders to gather requirements and deliver AI capabilities
• Write and execute test cases, debug, conduct code reviews, monitor production performance, and resolve issues
• Participate in model evaluation, deployment, monitoring, and optimization to improve performance, accuracy, latency, scalability, and cost efficiency
• Implement AI solutions in compliance with security, privacy, governance, Responsible AI, HIPAA, and enterprise data protection requirements
• Create and maintain technical documentation, solution designs, architecture diagrams, implementation guides, and operational runbooks
• Participate in Agile or SAFe planning, sprint activities, estimation, and continuous improvement
• Evaluate new AI technologies, frameworks, and cloud services and recommend improvements

Senior AI Engineer

• Design, build, and operationalize scalable, secure, and responsible Generative AI solutions across the affiliate line of business
• Develop and implement advanced machine learning models and algorithms for complex healthcare problems
• Collaborate with data scientists, clinicians, and IT professionals to define requirements and prioritize machine learning initiatives
• Define model performance metrics and evaluation methodologies
• Design and implement scalable machine learning systems, data pipelines, preprocessing, feature engineering, and model training
• Optimize data pipelines, model training processes, and infrastructure
• Present technical findings, insights, and recommendations to technical and non-technical stakeholders
• Ensure compliance with data privacy regulations, ethical guidelines, HIPAA, and industry standards
• Manage team performance through feedback and formal performance reviews
• Evaluate new machine learning algorithms and methodologies
• Build and deploy production-grade LLM and GenAI applications using AWS Bedrock and GCP Vertex AI
• Build cloud-native AI systems with serverless, event-driven, microservices, and API architectures
• Architect agentic AI systems and deliver multi-step reasoning, tool-use, and workflow orchestration
• Develop AI agents using Copilot Studio and Power Automate Cloud flows
• Develop RAG systems and secure document ingestion, embedding, chunking, grounding, and retrieval pipelines
• Lead model experimentation, fine-tuning, evaluation, deployment, and monitoring
• Optimize cost, performance, token usage, latency, and scaling
• Partner with product, engineering, data, security, and compliance teams
• Mentor engineers and contribute reusable patterns, frameworks, and platform accelerators

AI Engineer jobs in Connecticut

Senior AI Engineer

Staff AI Engineer