Artificial Intelligence Engineer

• Opening with a IT Co -
• 1- Based in Gurgaon
• 2- Udaipur

Job description

As an AI Engineer, you'll bridge the gap between AI research and production-ready systems. you'll 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 (eg, 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 (eg, NLP, computer vision) using frameworks like PyTorch/TensorFlow.
• Collaborate with data scientists to prototype and iterate on AI solutions.

Backend Development:

• Develop RESTful APIs withFastAPIto serve AI models at scale.
• Optimize database interactions usingPostgreSQLand ORM tools (eg, SQLAlchemy).

Tooling & Automation:

• UseCursorto 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 (eg, generative AI, vector search) and propose innovative solutions.
• Evaluate new tools/libraries to enhance our tech stack.

Requirements:

• Bachelor s/Master s in Computer Science, Engineering, or related field.
• 3+ yearsof hands-on experience in AI/ML engineering.
• Proficiency inPython,PostgreSQL, andFastAPI.
• Expertise inprompt engineeringand LLMs (eg, OpenAI, Anthropic).
• Experience usingCursorfor 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 (eg, 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.