Generative AI Engineer

The Generative AI Engineer will work with a cross-functional consulting team in Mumbai to design and build bespoke GenAI applications across industries. The role connects data scientists, ML engineers and platform engineers, helping customers choose cost-effective approaches ranging from semantic search and RAG to agents and fine-tuning. The position is onsite at the Mumbai office.

Responsibilities

• Understand customer requirements, benchmark candidate foundation models for use-case fit and cost-performance, prototype solutions, validate ideas and support both proofs of concept and enterprise-grade rollouts.
• Build LLM applications using models such as OpenAI, Claude and Mistral and frameworks including LangChain and LlamaIndex. Implement RAG pipelines with vector databases to ground responses in internal knowledge; develop text, audio and image solutions and autonomous agents where appropriate.
• Design reusable prompts and workflows using Chain-of-Thought, ReAct, Graph-of-Thought and agent flows. Tune prompt flows for reliability, relevance and user experience, and assess PEFT, LoRA and RLHF fine-tuning strategies for proprietary use cases.
• Deploy solutions on AWS, GCP or Azure, including services such as SageMaker, Bedrock and Vertex AI. Support ML CI/CD, drift detection, canary releases and retraining schedules; address observability, performance, security guardrails, GDPR compliance and Responsible AI. Integrate solutions into microservices and APIs with DevOps teams, and document frameworks, risks and best practices.

Qualifications

• Bachelor’s or master’s degree in computer science, AI or a related field; 5+ years of NLP/ML/AI experience, including at least 3 years of hands-on GenAI experience.
• Strong Python skills and experience with PyTorch, Hugging Face, LangChain and LlamaIndex; cloud AI services and APIs from OpenAI, Anthropic or Hugging Face; and vector databases such as Qdrant, pgvector, Pinecone, FAISS, Milvus or Weaviate. Familiarity with prompt engineering, transformers and embeddings is required, alongside problem-solving, collaboration and communication with technical and non-technical stakeholders.

The company offers training through internal programs and technology partners, leadership development programs, and opportunities to work on diverse AI projects.