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Mid LevelFull-timeReactNode.jsNext.jsAWSGCPDockerMicroservicesMachine LearningCI/CDAI
Salary Range
$102,000 - $138,000 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a talented Full Stack Engineer to collaborate with Motive stakeholders in designing, developing, and maintaining cutting-edge AI solutions and internal software. This position bridges engineering and product delivery, requiring both strong technical skills in AI/ML and the ability to work closely with business and technical teams.
Key Responsibilities
- →Build and deploy AI solutions seamlessly integrated into client workflows
- →Contribute to the design and optimization of AI pipelines
- →Create proof-of-concept solutions and support their transition to production-ready systems
- →Develop, implement, and deploy full-stack applications or microservices
- →Partner with Architects and Product teams to gather requirements and implement GenAI solutions
- →Rapidly build and refine proof-of-concepts based on feedback
- →Develop reusable components and enhance CI/CD pipelines
- →Ensure comprehensive documentation for codebases and internal tools
- →Translate business objectives into actionable technical tasks
- →Identify areas where AI can enhance existing workflows
- →Customize foundation models through fine-tuning and prompt engineering
- →Develop APIs and SDKs to connect AI systems with enterprise applications
- →Guarantee that solutions meet high standards for performance, reliability, and security
Requirements
- ✓3+ years of experience in software engineering, machine learning engineering, or applied AI roles
- ✓Solid understanding of large language models (LLMs) and generative AI principles
- ✓Proven ability to build APIs and work with distributed systems
- ✓Excellent communication skills
- ✓Background in customer-facing or collaborative engineering environments
- ✓At least 2 years developing production software with familiarity in front-end (React.js, Next.js) and back-end (Node.js) technologies
- ✓Hands-on experience with LLMs, prompt engineering, RAG pipelines, or vector databases
- ✓Working knowledge of AWS or GCP, Docker, and CI/CD pipelines
- ✓Ability to excel in fast-paced environments and adapt quickly to evolving requirements
