Lead AI Engineer I - R01571043

Analyst

Experience Range: With at least 2 to 4 years of experience in full-stack data science, including practical exposure to cloud-native architectures and agentic AI frameworks Key Responsibilities:

• Design and develop end-to-end full-stack applications, covering frontend, backend, and API components

• Build and deploy agentic AI applications using multi-agent systems and autonomous workflows

• Implement scalable backend systems with microservices and event-driven architectures to support intelligent solutions

• Develop cloud-native solutions on platforms such as Azure, AWS, and GCP, ensuring robust and scalable deployments

• Integrate LLM-based frameworks and agent orchestration tools to enable adaptive and intelligent workflows

• Enforce best practices in code quality, testing, debugging, observability, performance optimization, security, and scalability

• Collaborate with cross-functional teams to deliver technical solutions aligned with business requirements

• Contribute to design reviews and architectural decisions for AI-driven systems

Required Skills:

• Full-stack development with React, Angular, or Vue for frontend

• Backend development using Node.js, Java Spring Boot, or Python frameworks (FastAPI, Django)

• RESTful API design and microservices architecture

• Experience with Azure, AWS, and GCP cloud platforms

• Hands-on experience with Docker containers and Kubernetes

• CI/CD pipeline implementation

• Agentic AI frameworks such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, or CrewAI

• Prompt engineering and Retrieval-Augmented Generation (RAG) techniques

Preferred Skills:

• Familiarity with vector databases such as FAISS or Pinecone

• Knowledge of event streaming systems like Kafka or Pub/Sub

• Experience with federated learning or privacy-preserving algorithms

• Contributions to open-source projects or hackathons in AI/ML or full-stack domains

• Experience with model experimentation platforms such as Domino Datalabs or Databricks ML

Desired Qualifications:

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a closely related discipline

• Certification in cloud platforms (e.g., AWS Certified Machine Learning Specialty, Azure AI Engineer Associate, Google Cloud Professional Machine Learning Engineer)

• Certification in full-stack development or AI frameworks (e.g., Full Stack Web Development, TensorFlow Developer Certificate)

Additional Information: Location: Bangalore (Hybrid work arrangement)