Job Overview
We are looking for an experienced AI Tech Lead to lead the architecture, implementation, and delivery of enterprise AI applications, Generative AI solutions, and agent-based AI platforms. The ideal candidate should have strong hands-on experience in AI/ML engineering, LLM-based application development, cloud deployments, and modern MLOps/LLMOps practices.
This role requires someone who can independently design scalable AI solutions, work with onshore and offshore teams, translate business requirements into technical architecture, and ensure successful delivery of AI-driven applications.
Key Responsibilities
Lead the design, implementation, and delivery of AI and Generative AI applications.
Build end-to-end AI solutions using commercial and open-source tools.
Design agent-based AI platforms using frameworks such as LangGraph, AutoGen, and CrewAI.
Translate business objectives into technical requirements and AI solution designs.
Define AI reference architectures, roadmaps, best practices, and implementation standards.
Set up data pipelines, model training environments, CI/CD workflows, and monitoring frameworks.
Drive scalable deployment using Docker, Kubernetes, and cloud platforms.
Ensure application scalability, reliability, maintainability, performance, and security.
Manage AI project execution, technical planning, resource coordination, and delivery risks.
Oversee the complete AI application lifecycle from design to deployment and optimization.
Mentor engineering teams and lead technical knowledge-sharing sessions.
Mandatory Skills
Strong hands-on experience with LangGraph, AutoGen, and CrewAI.
Strong programming experience in Python.
Experience with TensorFlow, PyTorch, and Keras.
Strong knowledge of Deep Learning, NLP, RNN, CNN, LSTM, and Transformer-based models.
Experience with AWS, Azure, or Google Cloud Platform.
Experience with Docker, Kubernetes, Jenkins, and GitLab CI/CD.
Knowledge of Terraform and CloudFormation.
Experience with databases such as PostgreSQL, MongoDB, and Cassandra.
Strong understanding of REST APIs, GraphQL, Microservices, and distributed systems.
Experience with messaging systems such as Kafka and RabbitMQ.
Preferred Skills
Experience with Hugging Face and OpenAI APIs.
Hands-on experience in MLOps or LLMOps.
Experience with LLM fine-tuning using models such as GPT, Llama, or PaLM.
Experience with monitoring tools such as Prometheus, Grafana, and ELK Stack.
Cloud certifications in AWS, Azure, or GCP are preferred.
TOGAF certification is desirable.
Qualifications
Bachelor’s or Master’s Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
Minimum 10 years of experience in AI, Machine Learning, Data Engineering, or related technology domains.
Strong experience in enterprise-level AI application design and implementation.
Excellent communication skills and ability to work with US-based stakeholders.
Pay: ₹58,444.60 - ₹125,833.80 per month
Application Question(s):
- How many years of total experience do you have in AI, Machine Learning, or related domains?
- Have you built or delivered any Generative AI or agent-based AI applications in production?
- What is your Expected CTC, Current CTC and notice period
Work Location: Remote
