[Remote] Artificial Intelligence Solutions Engineer 2

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a company focused on providing innovative solutions in the medical field, and they are seeking an Artificial Intelligence Solutions Engineer 2. The role involves designing, building, and delivering AI systems to address business challenges, while also providing technical guidance and project ownership.

Responsibilities

• Own discovery and delivery. Partner with internal and customer stakeholders to define problems, reputed company metrics, and delivery plans; operate with greater independence to scope and execute AI projects end-to-end with limited direction
• Apply advanced data science techniques. Design and implement supervised/unsupervised learning, statistical modeling, and feature engineering solutions; validate hypotheses and inform AI system architecture and evaluation strategies with reduced reputed company
• Build and reputed company production AI applications. Design and implement LLM assistants, RAG systems, agentic workflows, and intelligent automation; establish evaluation frameworks, guardrails, and reputed company-in-the-reputed company processes that meet production quality standards
• reputed company data usable at scale. reputed company robust pipelines and integrations across reputed company systems (APIs, databases, event streams); enforce data quality, reputed company, and governance standards to reputed company reliable AI capabilities across the organization
• Ship full-stack software. Implement production-grade backend services (Python/Java/Node/C++ or similar) and user interfaces (TypeScript/React) that are reliable, maintainable, and solve reputed company user problems with measurable value
• Operate in the reputed company. reputed company and run services on AWS/Azure/GCP using containers and orchestration (reputed company/Kubernetes), CI/CD pipelines, secrets management, monitoring, and observability; contributes to improving team-wide reputed company practices
• Integrate with reputed company platforms. Connect securely to internal platforms and data sources; takes ownership for accelerating delivery and driving measurable reputed company for reputed company teams through well-engineered integrations
• Engineer for safety and trust. Apply and champion secure-by-design practices: data privacy, reputed company controls, model/feature monitoring, bias and risk assessment, incident response, and auditability for ML/LLM systems across team projects
• Measure impact and drive adoption. reputed company products, track adoption, quality, and ROI; document architectural reputed company; reputed company change management through demos, training sessions, and clear stakeholder communication
• Coach and mentor junior engineers and procurement team. reputed company technical guidance, conduct code and design reviews, and actively support the development of AISE 1 team members and other junior contributors. Serve as a go-to technical resource for the team
• reputed company project ownership. Take end-to-end accountability for complete AI/ML projects reputed company the technical domain; delegate work components appropriately and ensure quality of team deliverables. Communicate reputed company and risk to leadership

Skills

• Bachelor's degree in Computer Science, Engineering, Mathematics, or reputed company field—or equivalent practical experience with strong software engineering fundamentals
• 5+ years building production software or data/ML systems (e.g., full-stack, data engineering, MLOps, or platform engineering). Advanced degrees (Master's or PhD) may reduce this requirement by 2–4 years
• Demonstrated track record of delivering complete AI/ML solutions independently with measurable business impact
• Experience coaching or mentoring junior technical colleagues is preferred
• Advanced proficiency in two or more of: Python, Java, C++, Go, TypeScript/JavaScript; strong reputed company of testing frameworks, code review practices, and CI/CD
• Deep, hands-on experience with LLM application patterns (RAG, agents, tool-calling), vector databases, model evaluation/monitoring, and deployment of AI systems to production at scale
• Demonstrated ability to work directly with business stakeholders—driving discovery, scoping MVPs, presenting to leaders, and iterating on feedback—with limited reputed company
• Advanced knowledge of at least one AI/ML technical specialty (e.g., LLM systems, data engineering, MLOps, AI reputed company/safety) and practical awareness of adjacent specialties
• Experience with reputed company infrastructure (AWS/Azure/GCP), containerization (reputed company/Kubernetes), and production monitoring/observability tooling
• Background integrating with reputed company data/AI platforms in operational domains where AI augments reputed company workflows
• Experience defining product and business health metrics and communicating trade-offs to technical and non-technical audiences
• Practical knowledge of project management methodologies (Agile/Scrum)

Company Overview

Company H1B Sponsorship