Generative AI Engineer

2 weeks ago


Bengaluru, India GlobalLogic Full time

Job Title: Lead AI/ML Engineer (Generative AI & LLMs)Experience: 7–10 yearsLocation: Pan India ( GlobalLogic offices)Mode: 3 days onsite/weekPreference will be given to candidates who can join within 45 days.Description:We are seeking an experienced Lead AI/ML Engineer with a proven track record in Generative AI, LLM integration, and enterprise-scale AI initiatives. The role requires strong expertise in multimodal AI, multilingual systems, fine-tuning, and solution architecture. You will lead cross-functional teams to design, build, and scale AI solutions that serve tens of thousands of users, ensuring high accuracy, performance, and compliance in production environments.Key ResponsibilitiesLead the design and delivery of enterprise-scale Generative AI solutions (RAG pipelines, multilingual assistants, multimodal platforms).Drive advanced fine-tuning of LLMs (LoRA/PEFT) and manage large-scale model integration for custom enterprise use cases.Architect and deploy scalable AI/ML workflows leveraging multi-cloud platforms (Azure OpenAI, AWS SageMaker, GCP Vertex AI).Implement semantic search and embeddings-based solutions using Pinecone, FAISS, Weaviate, Milvus.Build robust APIs and services (REST, GraphQL, FastAPI, Flask, Django) for enterprise AI consumption.Apply end-to-end MLOps practices – CI/CD, retraining pipelines, monitoring, autoscaling, compliance, and cost optimization.Collaborate with stakeholders, product owners, and engineering leadership to align AI initiatives with business goals.Mentor and guide AI/ML engineers, fostering technical excellence and innovation across teams.Required SkillsProgramming: Python, PyTorch, TensorFlowFrameworks: LangChain, Hugging Face, LlamaIndex, Prompt Engineering, RAGCloud & DevOps: Docker, Kubernetes, MLflow, GitHub Actions, Azure OpenAI, AWS SageMaker, GCP Vertex AIDatabases: SQL/NoSQL, Vector DBs (Milvus, Pinecone, FAISS, Weaviate)API Development: REST, GraphQL, FastAPI, Flask, DjangoExpertise in enterprise-scale LLM integration, multimodal AI, multilingual platforms, and embeddings-based semantic searchGood to HaveExperience building enterprise AI assistants or multilingual AI platforms serving 50k+ users.Strong understanding of compliance, governance, and security requirements in enterprise AI deployments.Familiarity with reinforcement learning and evaluation metrics for LLMs.



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