Artificial Intelligence Engineer

Job Title :- Gen AI

Experience :-4+ yrs

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.