Gen AI Engineer

B.Tech/MCA with 3 - 7 years of Data Science experience, demonstrating strong expertise

in building robust AI/ML systems and scalable application architectures.

● At least 2+ years of focused, hands-on experience building and deploying practical

Generative AI applications, such as AI virtual assistants, complex AI agents, and content

generation tools.

● Spearheaded initiatives that improved operational efficiency and scalability, leading to

measurable gains in revenue growth and client acquisition.

● Proven experience utilizing core GenAI tools and platforms like AWS Bedrock (including

various foundation models and Bedrock Agents), LangChain, designing and

implementing RAG pipelines, leveraging Agent-based frameworks (e.g., CrewAI),

working with vector databases (e.g., Pinecone, Weaviate, Qdrant, Milvus, ChromaDB),

and understanding LLM principles. Experience with model training/fine-tuning (e.g.,

LoRA/QLoRA) and core NLP concepts is essential.

● High proficiency in Python and strong familiarity with modern ML/AI libraries (e.g.,

Hugging Face Transformers, PyTorch/TensorFlow, Scikit-learn, Pandas, NumPy) and

relevant SDKs (e.g., Boto3, OpenAI SDK).

● Demonstrated practical experience in developing, performance tuning, and optimising

LLM-based applications, including sophisticated prompt engineering techniques.

● Experience leveraging AI coding assistants (e.g., GitHub Copilot, Amazon Q, Cursor) to

accelerate development workflows while maintaining code quality.

● Deep understanding and practical application of data privacy principles, security best

practices, and cost-aware system design, specifically within the context of AI and

Generative AI applications.

● Strong understanding of working effectively with both structured and unstructured data,

including efficient retrieval, processing, and transformation techniques for GenAI.

● Proven ability to work effectively across diverse disciplines—collaborating seamlessly with

product, design, business, and other engineering teams in fast-paced, dynamic

environments.

● Hands-on experience developing and deploying applications on cloud platforms, with

AWS being highly preferred.

● Excellent analytical and problem-solving skills, coupled with a strong bias toward action,

experimentation, and continuous learning.

● Exceptional communication and collaboration skills, capable of articulating complex

technical concepts clearly to various audiences.