ExponentialAI - Artificial Intelligence Lead/Architect

Description :

Job Title : AI Architect / AI Lead

Experience Required : 10+ Year

Location : Hyderabad

Job Type : Full-Time

Job Overview :

Exponential AI is seeking an exceptional AI Architect/Ai Lead with 10+ years of experience to architect and lead our next-generation AI/ML initiatives. This role demands deep expertise in Generative AI, ML system design, and MLOps, combined with strong foundations in traditional ML, deep learning, and NLP. You will be responsible for designing scalable ML systems, building production-grade GenAI solutions, and establishing robust MLOps practices that enable rapid, reliable model deployment and monitoring.

Key Responsibilities :

GenAI & LLM Development :

- Lead the design, fine-tuning, and deployment of Large Language Models (LLMs) and Generative AI solutions using frameworks like LangChain, LlamaIndex, and Hugging Face

- Architect and implement RAG (Retrieval-Augmented Generation) pipelines, vector databases, and semantic search systems

- Optimize LLM performance through prompt engineering, fine-tuning techniques (LoRA, QLoRA), and efficient inference strategies

ML System Design & Architecture :

- Design end-to-end ML system architectures that are scalable, maintainable, and cost-effective

- Lead architectural decisions for real-time and batch inference systems, including model serving strategies

- Build robust feature stores, model registries, and data versioning systems

- Design distributed training pipelines for large-scale models and implement efficient model compression techniques

- Lead development of classical ML models, NLP solutions (including knowledge graphs), deep learning based applications

MLOps & Production Engineering :

- Establish and lead MLOps best practices including CI/CD pipelines for ML models, automated testing, and model monitoring

- Implement comprehensive model monitoring, drift detection, and automated retraining workflows

- Build observability systems for tracking model performance, latency, and data quality in production

- Design A/B testing frameworks and experimentation platforms for model evaluation

- Containerize and orchestrate ML workloads using Docker, Kubernetes, and cloud-native tools

- Design scalable data pipelines for feature engineering, data preprocessing, and model training using streaming and batch data processing frameworks (Spark, Kafka, Airflow)

Leadership & Collaboration :

- Mentor junior ML engineers and drive technical excellence across the team

- Collaborate with product, engineering, and business teams to translate requirements into ML solutions

- Lead technical design reviews and establish engineering standards and best practices

Required Skills :

GenAI & LLMs (Must-Have) :

- Hands-on experience with LLM frameworks (OpenAI API, Anthropic Claude, open-source models via Hugging Face)

- Proficiency in building RAG systems, prompt engineering, and LLM fine-tuning techniques

- Experience with vector databases (Pinecone, Weaviate, Chroma, FAISS) and embedding models

- Knowledge of LLM deployment and optimization (vLLM, TensorRT-LLM, quantization)

ML System Design & MLOps :

- Proven track record of designing and implementing production-scale ML systems

- Deep understanding of model serving architectures (REST APIs, gRPC, batch inference)

- Extensive experience with MLOps tools : MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML

- Proficiency in containerization (Docker) and orchestration (Kubernetes, AWS ECS/EKS)

- Experience building CI/CD pipelines for ML (GitHub Actions, Jenkins, GitLab CI)

- Expertise in model monitoring and observability tools (Evidently, Prometheus, Grafana)

- Production experience with cloud platforms (AWS, Azure, or GCP) and their ML services

Core ML & Programming :

- Expert-level Python programming with ML frameworks (PyTorch, TensorFlow, scikit-learn)

- Strong foundation in ML algorithms, deep learning architectures, and NLP techniques including knowledge graphs

- Proficiency in distributed computing frameworks (Ray, Dask, Spark)

- Experience with experiment tracking and hyperparameter optimization

Preferred Qualifications and Skills :

- Bachelor's or Master's degree in Engineering, Technology, Computer Science, Machine Learning, Operations Research, Statistics, Mathematics, or equivalent quantitative field

- 10+ years of solving and delivering business problems through machine learning, data science, AI, and statistical algorithms

- 6+ years of designing and implementing production-scale ML systems

- At least 3+ years focused on GenAI/LLMs and MLOps

- Demonstrated experience leading ML projects and mentoring engineering teams

- Familiarity with model governance, compliance, and responsible AI practices

- Experience with model deployment and optimization for resource-constrained environments

Why Join Exponential AI ?

- Cutting-Edge Innovation : Work on state-of-the-art GenAI and ML systems that push technological boundaries

- Ownership & Impact : Lead critical AI initiatives and shape the technical direction of our ENSO platform

- Competitive Compensation : Industry-leading salary and performance-based incentives

- World-Class Team : Collaborate with exceptional engineers and researchers in a culture of innovation

- Flexible Work Environment : Hybrid work model with modern infrastructure and tools