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AI Engineer
AI EngineerIntuitive Technology Partners, Inc. • San Francisco, CA, United States
AI Engineer

AI Engineer

Intuitive Technology Partners, Inc. • San Francisco, CA, United States
2 days ago
Job type
  • Full-time
Job description

About the job

Title : AI Engineer

Start Date : Immediate

Position Type : Full-time Employment

Location : Hybrid in San Francisco, US

Job Description

Overview : 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.

    • Success Essentials

  • Partner with AI leadership to shape the AI / ML roadmap and lead a team of AI engineers.
  • Architect and implement scalable AI systems to solve complex business problems.
  • Mentor and guide junior engineers and data scientists.
  • Ensure ethical, compliant, and innovative AI development.
  • Present technical results and engage with business partners to define project requirements.

    • How you will contribute

  • Conduct research, design, and develop generative AI‑driven features and experiences customized to the unique preferences and behaviors of our users.
  • Utilize cutting‑edge technologies such as machine learning, natural language processing (NLP), computer vision, and other AI methodologies to improve product functionality.
  • Collaborate effectively with cross‑functional teams to seamlessly integrate AI capabilities into existing products and pioneer the development of new AI‑powered solutions.
  • Work closely with product designers to define requirements, prioritize features, and craft intuitive user interfaces for AI‑powered features.
  • Implement, test, and deploy scalable machine learning solutions in production.
  • Stay current with the latest advancements in machine learning and artificial intelligence.

    • Who we are looking for

  • 4+ years’ experience in Machine Learning.
  • Minimum of 2 years of hands‑on experience in developing Agentic, LLM and NLP based applications.
  • Proficient in machine learning, deep learning, and generative AI techniques.
  • Experience with data preprocessing, feature engineering, and model evaluation techniques.
  • Proficiency in Python and SQL.
  • Strong understanding of software development methodologies, including agile development practices, version control systems, and CI / CD pipelines for ML.
  • Experience in applying supervised, unsupervised or reinforcement learning paradigms to business problems.
  • Proven track record of deploying AI models in production.
  • Experience with public cloud platforms (AWS, GCP or Azure) and containerization technologies (Docker, Kubernetes).
  • Strong problem‑solving skills to devise innovative and creative AI solutions.
  • Excellent communication and collaboration skills in a fast‑paced environment.

    • Apply Now

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