At Quest Global, it’s not just what we do but how and why we do it that makes us different. With over 25 years as an engineering services provider, we believe in the power of doing things differently to make the impossible possible. Spanning 18 countries and speaking 51 languages, our 21,000+ extraordinary employees are driven by the desire to make the world a better place.
Company: Quest Global
Role: AI Engineer II
Location: Pune, Maharashtra, India
Experience:
- Master's or Bachelor's degree in Computer Science, AI/ML, or Engineering, with significant hands-on experience leading and delivering complex Gen AI or ML engineering programs in production environments.
- Expert-level, hands-on experience designing, building, and deploying large language model (LLM) applications, agentic systems, and RAG pipelines — from prototype to production.
- Deep proficiency with LLM ecosystems: OpenAI, Anthropic, Gemini, Hugging Face, LangChain/LangGraph, and open-source foundation models (LLaMA, Mistral, Falcon, etc.).
- Strong command of Gen AI engineering patterns: prompt engineering, chain-of-thought reasoning, tool/function calling, vector embeddings, semantic search, and agent memory architectures.
- Solid applied knowledge of ML fundamentals — predictive modeling, deep learning (PyTorch, TensorFlow), and statistical techniques — used in tandem with Gen AI for hybrid, interpretable systems.
- Excellent Python engineering skills including async programming, API development (FastAPI), and building inference-ready microservices; SQL proficiency required.
- Hands-on experience with cloud AI infrastructure (AWS SageMaker, Bedrock, Azure OpenAI, or GCP Vertex AI) and familiarity with MLOps/LLMOps tooling (MLflow, Weights & Biases, etc.).
- Strong analytical, communication, and stakeholder management skills — with the ability to translate complex Gen AI concepts into business value and lead cross-functional teams toward delivery.
Qualification:
- Master's degree in Computer Science, AI/ML, or Engineering
- Bachelor's degree in Computer Science, AI/ML, or Engineering
Role Focus:
• Architect and lead the development of multi-agent AI systems
• Design and operationalize multimodal generative AI pipelines
• Build production-grade RAG and Graph-RAG systems
• Lead LLM fine-tuning, prompt engineering, and model alignment strategies
• Establish robust LLMOps and MLOps pipelines
• Develop high-performance Python backend services
• Engineer state, memory, and context management subsystems
• Implement Responsible AI and AI governance practices
• Apply traditional ML and statistical modeling in hybrid architectures
More skills:
Pinecone, pgvector, OpenSearch, Neo4j, AWS Neptune, Databricks, MLflow, FastAPI, AWS SageMaker, Bedrock, GCP Vertex AI, PyTorch, TensorFlow, SQL
Other:
- We believe that our company culture is the key to our ability to make a true difference in every industry we reach.
- Our teams regularly invest time and dedicated effort into internal culture work, ensuring that all voices are heard.
- We wholeheartedly believe in the diversity of thought that comes with fostering a culture rooted in respect, where everyone belongs, is valued, and feels inspired to share their ideas.
- We know embracing our unique differences makes us better, and that solving the worlds hardest engineering problems requires diverse ideas, perspectives, and backgrounds.