Remote Implementation Manager Jobs in Rochester, NY

We are seeking an AI Solutions Engineer to lead client AI initiatives from discovery through production deployment. You will partner with clients to identify high-impact Generative AI use cases, evaluate data readiness, and rapidly build proof-of-concept applications that demonstrate tangible business value. You will design and implement production-ready AI solutions leveraging Amazon Bedrock, foundation models, RAG pipelines, and AI agent frameworks such as LangChain and LlamaIndex. As a client-facing technologist, you will translate business requirements into technical architecture recommendations and guide clients on AI/ML best practices.

Location: This can be a remote opportunity, with 2 weeks of travel into Rochester, NY per quarter

What this role is responsible for:

AI Assessment & Discovery

• Participate in client discovery workshops and technical interviews to identify and prioritize high-impact GenAI use cases
• Analyze client data landscapes, evaluating data readiness, quality, and accessibility for AI solutions
• Rapidly design and build proof-of-concept (POC) applications and live demonstrations that validate AI use cases and illustrate business value to client stakeholders
• Translate discovery findings into technical specifications, architecture recommendations, and implementation plans
• Present POC results and assessment recommendations to client teams, building confidence and momentum for production investments

GenAI Solution Development

• Design and implement production-ready Generative AI applications using Amazon Bedrock, Anthropic Claude, and other foundation models
• Build and optimize RAG (Retrieval-Augmented Generation) pipelines with vector databases (Weaviate, OpenSearch, Pinecone)
• Develop AI agents and multi-agent orchestration systems using frameworks like LangChain, LlamaIndex, or custom implementations
• Create conversational AI interfaces with natural language understanding, intent detection, and context management
• Implement prompt engineering strategies, few-shot learning, and fine-tuning approaches for domain-specific applications

Client Engagement & Delivery

• Translate business requirements into technical specifications and suggested implementation plans
• Provide technical guidance and recommendations to clients on AI/ML best practices
• Document architecture decisions, code, and deployment suggestions

What makes someone successful in this role:

• You have a proven track record delivering production AI applications from concept to deployment
• You excel at conducting technical discovery and assessment work, including stakeholder workshops and use-case identification
• You can build proof-of-concept applications and live demonstrations that communicate technical concepts to non-technical audiences
• You have excellent problem-solving skills and the ability to work independently with minimal supervision
• You possess strong written and verbal communication skills for client-facing interactions
• You are passionate about Generative AI and stay current with the latest developments in LLMs, agents, and AI frameworks

Requirements:

• 5+ years of software engineering experience with at least 2+ years focused on AI/ML, data engineering, or cloud-native development
• 2+ years of hands-on AWS experience with production deployments
• 1+ years of direct Generative AI experience (LLMs, embeddings, RAG, agents)
• AWS Certifications: Solutions Architect Associate/Professional, Machine Learning Specialty, or Developer Associate (preferred)
• Background in healthcare, financial services, or regulated industries with understanding of compliance requirements (HIPAA, PCI-DSS, SOC 2) (preferred)
• Contributions to open-source AI/ML projects or published technical content (preferred)
• Experience with multi-tenant SaaS architectures and data isolation patterns (preferred)
• Knowledge of cost optimization strategies for AI workloads (model selection, caching, batching) (preferred)
• Familiarity with frontend frameworks (React, Angular) for building AI-powered UIs (preferred)