AI Architect (Remote, Contract, & Part-Time)
Company Description
Invene is a healthcare-focused AI and technology consulting firm that partners with payers, providers, and healthcare technology organizations to solve complex business and technical challenges. We specialize in designing, building, and deploying production-ready AI solutions that deliver measurable business value. Our work combines AI engineering, software development, data engineering, and technical strategy to help healthcare organizations move beyond AI experimentation into real-world implementation. We work directly with clients to understand their challenges, identify opportunities for AI, and develop solutions that can operate reliably at enterprise scale. This role will pay hourly between $100/hour to $200/hour depending on your skill-set, experience, and industry expertise. Role Description We are seeking a Senior AI Architect for a part-time, remote contract position. This is a hands-on technical role for someone who combines deep generative AI expertise, strong software engineering skills, and the ability to lead technical implementation within client engagements. You will work directly with clients to design, develop, experiment with, and deploy AI solutions that address real business challenges. You will be responsible for making key technical decisions, evaluating different approaches, and ensuring solutions are reliable, scalable, and cost-effective. This is not a traditional architecture-only or advisory position. We are looking for someone who can both design the solution and help build it. The ideal candidate is a senior engineer who enjoys solving ambiguous technical problems, experimenting with emerging AI capabilities, and turning successful prototypes into production-ready systems.
Key Responsibilities
Architect and implement AI solutions: Design and actively contribute to the development of production-grade generative AI applications, AI agents, document intelligence systems, and other AI-powered workflows. Lead technical execution: Own technical decisions within client engagements, collaborating closely with software engineers, data engineers, and client technical teams to deliver working solutions. Experiment and evaluate: Design and execute experiments to compare AI models, architectures, and approaches. Use measurable results to guide decisions about accuracy, performance, reliability, and cost. Adapt and extend existing solutions: Leverage existing AI components, frameworks, and production modules wherever possible, tailoring them to client-specific requirements rather than rebuilding solutions unnecessarily. Develop reusable AI capabilities: Identify opportunities to improve and extend shared AI components, helping turn solutions developed for individual clients into reusable capabilities. Collaborate directly with clients: Participate in technical working sessions, explain architectural decisions, demonstrate working solutions, and translate complex technical concepts into clear business implications. Optimize AI systems: Evaluate approaches involving LLMs, embeddings, retrieval, classification, and orchestration to select the right technology for each problem. Support production deployment: Work with engineering teams to ensure AI solutions meet requirements for security, scalability, maintainability, observability, and performance. Leverage AI development tools: Actively use modern AI-assisted development tools to accelerate engineering, experimentation, and delivery.
Qualifications
Required Qualifications Significant hands-on experience in software engineering, system architecture, and building production applications. Strong practical experience developing and deploying solutions using large language models (LLMs) and generative AI technologies. Deep understanding of AI concepts including embeddings, vector similarity, retrieval techniques, model inference, and the trade-offs between different AI architectures. Demonstrated ability to design technical experiments, establish evaluation criteria, interpret results, and make evidence-based architectural decisions. Strong programming skills, particularly in Python, with experience building APIs, services, and integrations. Experience developing AI solutions beyond proof-of-concept, including consideration of production reliability, latency, cost, and performance. Ability to independently solve complex, ambiguous technical challenges and take ownership of technical execution. Strong communication skills and experience working directly with clients or business stakeholders to explain technical decisions and demonstrate solutions. Practical experience using AI-assisted coding tools as part of everyday software development.
Preferred Qualifications
Experience developing AI agents, multi-step LLM workflows, document processing systems, or intelligent automation solutions. Experience with embedding-based classifiers, semantic search, retrieval-augmented generation (RAG), and alternative approaches to knowledge retrieval. Strong understanding of machine learning fundamentals, neural networks, transformer architectures, and modern generative AI capabilities. Experience designing reusable AI components, frameworks, or shared services used across multiple applications or clients. Experience with cloud infrastructure and deploying AI applications on AWS, Azure, or GCP. Familiarity with healthcare technology, clinical data, HIPAA, or regulated enterprise environments. Experience in consulting, professional services, or other client-facing technical delivery environments.
What We're Looking For
We're looking for someone who is intellectually curious, technically rigorous, and highly execution-oriented. The right candidate doesn't simply recommend using an LLM for every problem. They understand how AI systems work, know when simpler approaches are better, and can design experiments to validate their decisions. They are equally comfortable discussing architecture with senior technical stakeholders, writing code alongside engineers, and demonstrating a working solution to a client. Most importantly, they take ownership of getting solutions into production, not just designing them.