AI/ML Solutions Architect
USA
Delivery – Rinat Gareev /
Full-time /
Remote
Provectus helps companies adopt ML/AI to transform the ways they operate, compete, and drive value. The focus of the company is on building ML Infrastructure to drive end-to-end AI transformations, assisting businesses in adopting the right AI use cases, and scaling their AI initiatives organization-wide in such industries as Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, Manufacturing, and Internet businesses.
We are seeking an experienced and independent AI/ML Solutions Architect to lead transformative AI initiatives that enhance automation, efficiency, and intelligent decision-making in high-throughput laboratory environments and enterprise solutions.
This is both a customer-facing and hands-on role, where you'll work across every stage of the ML/AI solution development lifecycle – from gathering requirements to production deployment and post-production maintenance. You'll work cross-functionally with teammates, including ML/data/DevOps engineers, to deliver bespoke AI solutions while acting as a strategic technical leader for large-scale AI/ML implementations.
Responsibilities:
- ML/AI Adoption & Strategy. Deploy ML and GenAI technologies for workflow automation and optimization. Engage in practical R&D across topics including Retrieval-Augmented Generation (RAG), LLM pipelines, LLM fine-tuning, and evaluation of LLM-based applications. Define and drive technical strategies that align AWS AI/ML capabilities with customer objectives.
- AI & Machine Learning Solution Architecture & System Design. Design and scale AI solutions using AWS services (like Bedrock, SageMaker) and open-source standards and frameworks. Lead the implementation of solutions on top of cloud platforms, ensuring quality, scalability, security, and cost-efficiency. Integrate AWS AI/ML services with in-house or 3rd-party solutions as needed.
- AI & Machine Learning Engineering & MLOps. Build and deploy model training, evaluation, and inference pipelines. Apply MLOps best practices. Productionize proof-of-concepts.
- Pre-Sales & Customer Engagement. Lead high-impact customer engagements focused on applying AI/ML to a variety of use cases in the healthcare and life sciences domain. Design and execute quick proofs of conceptsPartner with the sales team, providing technical expertise to position AI/ML solutions effectively. Create technical proposals, solution architectures, and presentations to support sales efforts. Demonstrate AWS AI/ML capabilities through POCs and technical demonstrations.
- Project Leadership & Delivery. Oversee the end-to-end implementation of bespoke AI/ML solutions, coordinating an engineering team to ensure successful delivery. Lead discovery workshops to understand customer requirements, success criteria, and technical constraints.
- "Swiss Army Knife" Engineering. During those occasional "all hands on deck" moments, jump in to support the team with backend/frontend development, infrastructure, or data pipelines as needed. Be able to quickly prototype functional solutions for demos and proof-of-concepts.
- Cross-Functional Collaboration & Thought Leadership. Collaborate with data scientists, engineers, and lab experts to design and improve AI solutions. Champion ethical and compliant AI practices aligned with healthcare and life sciences regulations. Maintain client-facing responsibilities with the ability to own processes and adapt to changing requirements. Build and maintain strong relationships with key customer stakeholders, acting as a trusted advisor for AI/ML platform initiatives.
- Innovation & Mentorship. Stay up-to-date with the latest developments in cloud technologies, MLOps, and GenAI frameworks. Develop and promote best practices for building AI/ML solutions.
Qualifications:
- 7+ years in software development with a strong focus on AI/ML engineering
- Deep expertise in Python, SQL, and frameworks like PyTorch/TensorFlow.
- Proven hands-on experience in Generative AI systems and their evaluation, plus RAG optimization.
- 3+ years designing and implementing large-scale AI/ML solutions in the cloud (AWS is preferred but not required).
- Deep expertise in AWS AI/ML platform services, including SageMaker and Bedrock.
- Expertise in core AWS services, including Lambda, S3, and SQS.
- Strong grasp of MLOps, scalability, and cloud (AWS) best practices.
- Technical sales or pre-sales experience with cloud AI/ML solutions.A builder mindset that is able to switch between fast prototyping and production-grade development.
- Good communication and presentation skills, with the ability to convey complex technical concepts to non-technical stakeholders.
- Experience working with LIMS/LES systems and lab automation tools.
- Familiarity with healthcare and life sciences regulatory requirements (e.g., HIPAA, GxP).Background in designing secure and compliant AI solutions for regulated environments.
- Experience in the Healthcare and Biotech domains.
- Certifications in AWS, Databricks, GCP, or Azure AI/ML services.
- Contributions to open-source AI/ML projects or active participation in the AI/ML community.
Required Experience:
Preferred Qualifications:
What We Offer:
- Remote-first work environment with flexible scheduling.
- Opportunity to contribute to high-stakes projects for mid-sized and large corporations.
- Collaborative culture that values innovation, curiosity, and continuous learning.
- Professional development support.
- Comprehensive benefits, including health, dental, vision, 401(k) with company match, and unlimited PTO.
- Diverse professional network across industries and technology domains.
