BISSELL Homecare, Inc. · 2 hours ago
Principal AI Full-Stack Developer
Grand Rapids, MI
Full-time
Onsite
Lead/Staff
15+ years expBISSELL Homecare, Inc. is seeking a Principal AI Full-Stack Developer with a strong foundation in software engineering to design, develop, and deploy intelligent applications that leverage AI capabilities. The role involves owning the full lifecycle of AI-enabled solutions and collaborating with various teams to embed AI into business workflows and accelerate AI-first engineering practices.
Manufacturing
Responsibilities
Own the full lifecycle of AI-enabled solutions, from ideation and architecture to deployment and ongoing optimization
Design, develop, and maintain full-stack applications that integrate AI/LLM capabilities into user-facing and backend systems
Architect and implement AI integrations using platforms and frameworks such as OpenAI, Azure OpenAI, AWS Bedrock, Gemini, and similar orchestration frameworks
Influence long-term AI roadmap decisions, advising executive leadership (VP/CIO, CTO) on platform strategy, model lifecycle planning, and capability investments
Leadership of an AI Engineering Guild and Community of Practice. Mentor and coach developers, analysts, and automation engineers on AI-first engineering patterns, tools, and best practices
Work closely with Enterprise Architecture and co-lead design reviews and approve architectural decisions related to AI systems, data flows, security boundaries, and integration patterns
Build, deploy, and maintain AI agents as part of full-stack, production-grade software systems
Integrate AI agents with all development and operational tools (e.g., Linear, GitHub, Datadog, Sentry, internal platforms) to maximize context and productivity. Proactively address and resolve any access barriers that limit agent effectiveness
Build scalable backend services using Node.js and Python
Develop modern, responsive front-end applications using React
Design and maintain RESTful and event-driven APIs that expose AI-driven functionality
Collaborate with Automation and Platform teams to embed LLMs into automated workflows and enterprise processes
Apply strong software engineering fundamentals (data structures, algorithms, design patterns, and clean architecture) when building AI-enabled systems
Ensure all AI-powered features leverage the latest generation models, migrating off legacy models as soon as robust evaluations support the change. Maintain a rapid upgrade cadence to maximize product performance and value
Lead technical enablement efforts by creating reusable AI components, SDKs, internal tooling, and reference architecture
Champion AI engineering best practices, including prompt engineering, evaluation strategies, versioning, observability, and responsible/ethical AI use
Support cloud-native deployment of AI-enabled applications across AWS, Azure, or GCP environments
Architect and oversee the implementation of advanced AI solutions, including multi-agent systems and generative AI platforms
Lead technical due diligence for new AI technologies and vendors
Implement embedding-based semantic search across all product surfaces, replacing legacy fuzzy search algorithms for superior relevance and accuracy
Stay current with emerging AI technologies and assess their applicability to enterprise software solutions
Deliver production-ready, maintainable, and secure AI-enabled applications aligned with enterprise standards
Ensure AI solutions meet requirements for availability, performance, scalability, security, and compliance
Drive standardization of AI development patterns, deployment pipelines, and operational practices
Empower engineering teams to select and utilize the most effective coding agents and harnesses—including Claude, Cursor, Devin, and both open and closed models. Ensure all engineers have access to the latest agent technologies and are not restricted by tooling or context limitations
Influence and implement cloud governance, security, and compliance strategies related to AI workloads
Champion an AI-first engineering culture and mentor junior engineers and contribute to internal standards, documentation, and knowledge-sharing initiatives
Foster an AI-first engineering culture by building primitives for model invocation and sandboxed code execution
Invest in comprehensive agent documentation tailored to your codebase. Continuously improve agent.md files, linting rules, and prompt strategies to optimize agent performance and minimize manual interventions
Prioritize advanced prompt engineering over custom model finetuning, adapting quickly to frontier model improvements and cost reductions
Qualification
Required
Enterprise Cloud Architecture & Strategy: Expertise in designing, implementing, and optimizing cloud-based architectures at scale
Technical Leadership & Mentorship: Proven ability to lead engineering teams and mentor talent across multiple disciplines
Automation & Infrastructure as Code: Strong background in automating cloud environments using Terraform, CloudFormation, or similar tools
Security & Compliance: Deep understanding of cloud security frameworks, regulatory compliance, and risk management
Problem-Solving & Decision-Making: Ability to analyze complex technical issues, provide innovative solutions, and drive decision-making
Strategic Vision & Business Alignment: Ability to align AI + cloud strategies with business goals and drive digital transformation
Collaboration & Communication: Exceptional ability to communicate technical concepts to both engineering teams, business owners and executive leadership
Continuous Learning & Innovation: Passion for staying ahead of AI & cloud technology trends and industry advancements
Bachelor's or master's degree in computer science, Software Engineering, Information Technology, or a related field
Equivalent real-world experience may be considered in place of a degree
15+ years of experience in software development, cloud architecture, and DevOps
1+ year of hands-on AI engineering experience, ideally in an enterprise or startup setting
Proven experience with AI development tools (e.g., Claude, GPT-4, etc)
Experience with AI/ML frameworks or services (e.g., OpenAI, Azure OpenAI, TensorFlow, PyTorch)
Experience with AI agents, agentic workflows and autonomous AI systems
Experience deploying applications and AI workloads to cloud environments
Strong understanding of application architecture, APIs, and microservices
Contributions to open-source AI projects or internal AI platforms
Deep expertise in cloud platforms (AWS, Azure, Google Cloud)
Strong proficiency in programming languages
Strong expertise in CI/CD automation (Jenkins, GitHub Actions, GitLab CI/CD)
Experience with cloud security, IAM policies, encryption, and compliance frameworks
Strong background in API development, integration, and microservices architecture
Experience with cloud networking (VPCs, load balancers, DNS, VPNs)
Proficiency in monitoring, logging, and observability (CloudWatch, Prometheus, Datadog)
Strong ability to lead and influence technical discussions across the organization
Preferred
AWS Certified Solutions Architect - Professional or AWS DevOps Engineer - Professional
Microsoft Certified: Azure Solutions Architect Expert
Agent Framework Training Certificates
Certified Kubernetes Administrator (CKA) or Certified Kubernetes Security Specialist (CKS)
Company
BISSELL Homecare, Inc.
We may be a company full of neat freaks. And that’s fine with us.
1001-5000 employees
Funding
Current Stage
Late StageLeadership Team
Adam Madigan
President and Chief Operating Officer
Recent News
Business Insider
2025-12-19
Company data provided by crunchbase