AI Full Stack Engineer
il y a 4 jours
San Francisco
About us: Intuitive.Cloud is one of the fastest-growing (INC 5000, CRN) Cloud & SDx solution and services companies supporting enterprise customers on a global scale. Intuitive is an "Engineering Company" delivering measurable value and key business outcomes. Intuitive Superpowers: • DataOps & AI/ML, • Cloud Native, AppSecOps, DevSecOps, • Cloud Migration & Transformation, • Cloud FinOps, • Cybersecurity (App/Data/Infra) & GRC, • SDx & Digital Workspace We are proud to partner with some of the world's leading enterprises and serve 200+ customers across different industry verticals. We have achieved many milestones along the way, including being recognized as a top-10 fast-growth 150 IT company in the Americas by CRN in 2022 and being named one of America's fastest-growing private companies by INC 5000 in 2022. That’s not all! Even CIO Review awarded us as the Most Promising Cloud Migration Company and Artificial Intelligence Solutions Provider in 2022. About the job: Title – AI Full Stack Engineer Start date: Immediate Position Type: Contract/ FTE Location: San Francisco, CA (Hybrid) Overview (infra) As an AI Engineer, you will play a pivotal role in designing, developing, and deploying domain-specific AI agents and solutions that drive organizational transformation. You’ll collaborate with cross-functional teams, lead technical initiatives, and ensure the delivery of scalable, production-ready AI systems. Key Responsibilities AI Development & Solution Delivery • Research, design, and develop generative AI-driven features and experiences tailored to user preferences and behaviours., • Build, prototype, iterate, and deploy domain-specific AI agents capable of communication, information gathering, insight generation, and intelligent actions., • Architect and implement scalable AI systems, including feature pipelines, model stores, and frameworks for reproducible research., • Lead end-to-end development of AI infrastructure and applications, from proof-of-concept to production deployment and ongoing maintenance., • Implement automated systems for continuous training, validation, and monitoring of models to ensure reliability and minimize downtime., • AI applications development aid with improvements in evaluation, prompt engineering, and AI interface Collaboration & Leadership • Work closely with product designers, managers, data engineers, and business stakeholders to define requirements, prioritize features, and align AI initiatives with business goals., • Collaborate with transformation teams and AI platform teams to build scalable, cross-domain AI agents and solutions., • Mentor junior AI engineers and data scientists, conduct code reviews, and promote best practices in AI development., • Provide guidance on data science best practices and advise on emerging AI technologies, frameworks, and tools., • Integration & Deployment, • Deploy, monitor, and optimize AI agents on cloud infrastructure (GCP, Azure), ensuring high availability and performance., • Build APIs, microservices, and data integrations for AI features, following industry best practices for maintainable code., • Ensure ethical AI development and compliance with data privacy regulations. Continuous Learning & Innovation • Stay current with advancements in AI, machine learning, and software engineering, integrating new technologies into existing or new AI agents., • Drive experimentation and innovation by evaluating and recommending cutting-edge AI technologies., • Conduct thorough testing and validation to ensure reliability and accuracy of AI solutions. Qualifications • Master’s or PhD in Computer Science, Mathematics, Physics, Statistics, or a related quantitative field., • 5–7 years’ experience in data science, machine learning, or AI, with a proven track record of deploying models in production environments., • Minimum 4 years’ experience in machine learning; at least 2 years hands-on with Agentic, LLM, and NLP-based applications., • Proficiency in Python and SQL; production-quality OOP skills (Python, C++, etc.)., • Experience with ML frameworks (TensorFlow, PyTorch)., • Strong understanding of software development methodologies (agile, version control, CI/CD pipelines for ML)., • Experience with public cloud platforms (GCP, Azure) and containerization (Docker, Kubernetes)., • Hands-on experience building ML solutions from inception to launch, including MLOps/AIOps infrastructure., • Solid grasp of data structures, algorithms, and software engineering principles., • Experience in supervised, unsupervised, or reinforcement learning paradigms., • Excellent problem-solving, analytical reasoning, communication, and collaboration skills., • Interest in prompt engineering, AI safety, and scalable deployment., • Ability to work cross-functionally and communicate solutions that meet business objectives., • Travel may be required for team collaboration, conferences, or vendor meetings.