Job Title: Lead AI/ML Engineer (Generative AI & LLMs)
Experience: 7–10 years
Location: Pan India ( GlobalLogic offices)
Mode: 3 days onsite/week
Preference 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 Responsibilities
- Lead 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 Skills
- Programming: Python, PyTorch, TensorFlow
- Frameworks: LangChain, Hugging Face, LlamaIndex, Prompt Engineering, RAG
- Cloud & DevOps: Docker, Kubernetes, MLflow, GitHub Actions, Azure OpenAI, AWS SageMaker, GCP Vertex AI
- Databases: SQL/NoSQL, Vector DBs (Milvus, Pinecone, FAISS, Weaviate)
- API Development: REST, GraphQL, FastAPI, Flask, Django
- Expertise in enterprise-scale LLM integration, multimodal AI, multilingual platforms, and embeddings-based semantic search
Good to Have
- Experience 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.