Generative AI Engineer
Sia (company site, opens in a new tab)5+ yrsMumbaiOn-siteDirect career pageEst. 20–35 LPA
Posted on 28 Sept
Reach people at Sia
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Sia you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design and build scalable Generative AI applications and solutions using large language models (LLMs) across diverse industries.
- Implement and optimize GenAI workflows including prompt engineering, RAG pipelines with vector databases, multimodal AI and autonomous agents.
- Manage deployment and operationalization of AI models ensuring security, compliance, performance monitoring, and integration with microservices and APIs.
Minimum Requirements
- 5+ years experience in NLP/ML/AI with at least 3 years hands-on experience in Generative AI.
- Strong coding skills in Python and experience with frameworks like PyTorch, Hugging Face, LangChain, LlamaIndex.
- Proven experience deploying AI models on cloud platforms (AWS/GCP/Azure) and familiarity with vector databases such as Pinecone, FAISS, pgvector, etc.
- Bachelor’s or Master’s degree in Computer Science, AI, or related field; role is Mumbai-based onsite.
Ideal Candidate Profile
- Experienced in building end-to-end GenAI products including prompt engineering, fine-tuning, and deploying at scale in cloud environments.
- Comfortable working collaboratively in cross-functional teams including data scientists, ML engineers, and platform teams to deliver enterprise-grade AI solutions.
- Ability to assess model benchmarking, cost-performance tradeoffs, and to translate complex technical concepts for varied stakeholder groups.