Generative AI Engineer

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.
Skills: retrieval-augmented generation (rag),supabase,docker,rag,gcp,azure,flask,asynchronous programming,postgresql,generativeai,aws,pytest,pgvector,langchain,pinecone,genai,fastapi,weaviate,mysql,python,llama-index,django,llm