AI Solutions Engineer

United States·Reports Into RochesterRemoteFull-Timemid

OtherAi Solutions Engineer

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Requirements Summary

This can be a remote opportunity, with 2 weeks of travel into Rochester,

Technical Tools

OtherAi Solutions Engineer

~1 min read

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)

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

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

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

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