As an AI Engineer, youll bridge the gap between AI research and production-ready systems. Youll design, develop, and deploy AI models while ensuring seamless integration with robust backend infrastructure. Your expertise in prompt engineering, Cursor (AI-assisted code editor), PostgreSQL, Python, and FastAPI will be critical to delivering scalable, performant solutions. This role requires staying ahead of industry trends, including advancements in LLMs, vector databases, and MLOps.
Key Responsibilities:
Prompt Engineering & LLM Optimization :
Design, test, and refine prompts for large language models (e.g., GPT-4, Claude, Deepseek, Gemini) to achieve optimal performance.
Implement retrieval-augmented generation (RAG) and fine-tuning strategies for domain-specific tasks.
AI Model Development :
Build, train, and deploy machine learning models (e.g., NLP, computer vision) using frameworks like PyTorch/TensorFlow.
Collaborate with data scientists to prototype and iterate on AI solutions.
Backend Development :
Develop RESTful APIs with FastAPI to serve AI models at scale.
Optimize database interactions using PostgreSQL and ORM tools (e.g., SQLAlchemy).
Tooling & Automation :
Use Cursor to streamline coding workflows, debug efficiently, and maintain code quality.
Integrate tools like LangChain, Pinecone, or Hugging Face into production pipelines.
Market & Trend Analysis :
Stay updated on AI advancements (e.g., generative AI, vector search) and propose innovative solutions.
Evaluate new tools/libraries to enhance our tech stack.
Requirements:
Bachelors/Masters in Computer Science, Engineering, or related field.
3+ years of hands-on experience in AI/ML engineering.
Proficiency in Python , PostgreSQL , and FastAPI .
Expertise in prompt engineering and LLMs (e.g., OpenAI, Anthropic).
Experience using Cursor for code optimization and pair programming.
Strong understanding of cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes).
Familiarity with version control (Git) and CI/CD pipelines.
Preferred Qualifications:
Certifications in AI/ML (e.g., AWS ML Specialty, TensorFlow Developer).
Experience with vector databases (Pinecone, Chroma) or MLOps tools (MLflow, TFX).
Contributions to open-source AI projects or publications in ML conferences.
What We Offer:
Competitive salary + equity (based on experience).
Flexible remote/hybrid work model.
Access to cutting-edge AI tools and training resources.
Collaborative, innovation-driven environment.
Professional development budget for conferences/courses.