GenAI Engineer Python

Job Title:

Experience:

Location:

We are seeking a skilled Generative AI Engineer with a strong background in Python to join our dynamic team. In this role, you will integrate backend development expertise with the latest advancements in AI to create impactful solutions. If you excel in a fast-paced environment and enjoy tackling complex challenges, we encourage you to apply.

Key Responsibilities:

Generative AI Development

• Develop and implement generative AI models using frameworks like LangChain or Llama-Index.
• Apply

  prompt engineering techniques

  to design effective queries and ensure optimal LLM responses for diverse use cases.
• Master advanced LLM functionalities, including

  prompt optimization

  , hyperparameter tuning, and response caching.
• Implement Retrieval-Augmented Generation (RAG) workflows by integrating

  vector databases

  like Pinecone, Weaviate, Supabase, or PGVector for efficient similarity searches.
• Work with embeddings and build solutions that leverage similarity search for personalized query resolution.
• Explore and process multimodal data, including image and video understanding and generation.
• Integrate observability tools for monitoring and evaluating LLM performance to ensure system reliability.

Backend Engineering

• Build and maintain

  scalable backend systems

  using Python frameworks such as FastAPI, Django, or Flask.
• Design and implement

  RESTful APIs

  for seamless communication between systems and services.
• Optimize database performance with relational databases (PostgreSQL, MySQL) and integrate

  vector databases

  (Pinecone, PGVector, Weaviate, Supabase) for advanced AI workflows.
• Implement

  asynchronous programming

  and adhere to

  clean code principles

  for maintainable, high-quality code.
• Seamlessly integrate

  third-party SDKs and APIs

  , ensuring robust interoperability with external systems.
• Develop backend pipelines for handling

  multimodal data processing

  , and supporting text, image, and video workflows.
• Manage and schedule background tasks with tools like Celery, cron jobs, or equivalent job queuing systems.
• Leverage containerization tools such as Docker for efficient and reproducible deployments.
• Ensure security and scalability of backend systems with adherence to

  industry best practices.

Qualifications:

Essential:

• Strong Programming Skills:

  Proficiency in Python and experience with backend frameworks like FastAPI, Django, or Flask.

• Generative AI Expertise:

  Knowledge of frameworks like LangChain, Llama-Index, or similar tools, with experience in prompt engineering and Retrieval-Augmented Generation (RAG).

• Data Management:

  Hands-on experience with relational databases (PostgreSQL, MySQL) and vector databases (Pinecone, Weaviate, Supabase, PGVector) for embeddings and similarity search.

• Machine Learning Knowledge:

  Familiarity with LLMs, embeddings, and multimodal AI applications involving text, images, or video.

• Deployment Experience:

  Proficiency in deploying AI models in production environments using Docker and managing pipelines for scalability and reliability.

• Testing and Debugging:

  Strong skills in writing and managing unit and integration tests (e.g., Pytest), along with application debugging and performance optimization.

• Asynchronous Programming:

  Understanding of asynchronous programming concepts for handling concurrent tasks efficiently.

Preferred:

• Cloud Proficiency:

  Familiarity with platforms like AWS, GCP, or Azure, including serverless applications and VM setups.

• Frontend Basics:

  Understanding of HTML, CSS, and optionally JavaScript frameworks like Angular or React for better collaboration with frontend teams.

• Observability and Monitoring:

  Experience with observability tools to track and evaluate LLM performance in real-time.

• Cutting-Edge Tech:

  Awareness of trends in generative AI, including multimodal AI applications and advanced agentic workflows.

• Security Practices:

  Knowledge of secure coding practices and backend system hardening.

• Certifications:

  Relevant certifications in AI, machine learning, or cloud technologies are a plus.