Job Summary
To be responsible for managing technology in complex projects ,providing technical guidance and ensuring successful delivery of solutions.
We are seeking a highly skilled and motivated Generative AI Engineer to join our dynamic team. In this role, you will be instrumental in designing, developing, and deploying cutting-edge applications powered by Generative AI. You will work in close collaboration with the Lead Engineer to bring complex, high-impact use cases from proof-of-concept to production.
The ideal candidate is a hands-on builder with a deep understanding of modern AI application architectures like multi-agentic and a practical grasp of the underlying infrastructure required to support them. If you are passionate about solving real-world problems by bridging the gap between powerful language models and robust software engineering, this is the perfect opportunity for you.
Key Responsibilities
• Design and Build GenAI Solutions: Collaborate on the end-to-end development of Generative AI applications, including system design, model integration, and back-end logic.
• Implement Advanced RAG Pipelines: Engineer and optimize sophisticated Retrieval-Augmented Generation (RAG) systems. This includes selecting appropriate embedding models, setting up and managing vector databases, and refining context retrieval and ranking strategies to ensure response accuracy and relevance.
• Manage Application Architecture: Take ownership of the technical architecture for various GenAI use cases, ensuring they are scalable, reliable, and efficient.
• Collaborate and Innovate: Work closely with the Lead Engineer to brainstorm new ideas, experiment with emerging technologies, and continuously improve our existing solutions.
• Stay Current: Keep up-to-date with the latest advancements in the rapidly evolving field of Generative AI and advocate for the adoption of best practices and new technologies.
Required Skills and Qualifications
• Proven GenAI Experience: Demonstrable experience building and deploying applications that leverage Large Language Models (e.g., OpenAI GPT series, Llama, Gemini, Claude).
• Strong Python Proficiency: Expertise in Python and core AI/ML libraries such as LangChain, LlamaIndex, Hugging Face, and PyTorch/TensorFlow.
• Deep RAG Expertise: A thorough, hands-on understanding of the entire Retrieval-Augmented Generation (RAG) architecture and workflow. You must be able to explain how context is ingested, retrieved, and utilized to mitigate model hallucinations along with different RAG chunking patterns and such.
• Vector Database Knowledge: Practical experience with vector stores like Pinecone, Weaviate, Chroma, or similar technologies.
• Strong Problem-Solving Skills: Ability to tackle complex technical challenges independently and collaboratively.
Preferred Qualifications
• Experience with developing multi-agent systems using frameworks like AG2 or CrewAI or any other framework.
• Familiarity with LLM fine-tuning techniques (e.g., LoRA).
• Experience with Azure and their associated AI/ML services.
• A portfolio of GenAI projects (e.g., GitHub repository) is a strong plus.
• Excellent communication skills and a collaborative mindset.
Key Responsibilities
2. To conduct comprehensive code reviews, establish and oversee quality assurance processes, performance optimization , implementation of best practices and coding standards to ensure successful delivery of complex projects.
3. To ensure process compliance in the assigned module| and participate in technical discussions/review as a technical consultant for feasibility study (technical alternatives, best packages, supporting architecture best practices, technical risks, breakdown into components, estimations).
4. To collaborate with stakeholders to define project scope, objectives, deliverables and accordingly prepare and submit status reports for minimizing exposure & closure of escalations.