Senior Analyst-Automation

What You Bring
 
Degree in Computer Science or related field
•    4 to 7 years of working experience as a software developer in AI-focused cloud/container application development.
•    A solid foundation in computer science, with strong competencies in algorithms, data structures, objects-oriented programming, design patterns, multi-threaded programming, and software design principles
•    Sound experience in cloud native development
•    Strong coding development and debugging skills, including hands-on experience with Java, JavaScript, GoLang and Python.
•    Hands-on experience in developing REST APIs using frameworks such as Flask, FastAPI etc.

•    Strong background with Java or JavaScript/TypeScript development building scalable APIs using Spring Boot, Node.js, Knowledge of Angular/React/Vue.js

•    Strong background in machine learning and deep learning algorithms. - Proficiency in Python, TensorFlow, and PyTorch, Huggingface for developing AI models.

Generative AI frameworks – Langchain, LlamaIndex,

Agentic Frameworks - AutoGen, Semantic kernel, crewAI, promptflow,Langflow, Langraph

•    Deep understanding of transformer architectures and diffusion models

•    Experience in generative AI techniques such as GANs and VAEs. - Ability to design and implement scalable and efficient AI systems.
•   Experience working with DevOps including but not limited to container technologies like Docker & Kubernetes, as well as Cloud Native technology stack such as Argo, Helm, etcd, and Envoy

•    Hands-on experience with frontend frameworks (React, Angular, Vue) and backend technologies (Node.js, Django, Flask).  

•    Cloud platforms (AWS, Azure) and containerization tools (Docker, Kubernetes).  

•    Strong understanding of database technologies (SQL, NoSQL, vector databases,Graph databases).  
•    Knowledge of prompt engineering, fine-tuning, and embeddings for AI applications.  
•    Familiarity with MLOps tools like MLflow, Kubeflow, or SageMaker.  
•    Prior experience deploying AI-driven applications in production environments.  
•    Experience working with message queues such as Kafka and a clear understanding of pub-sub systems is bonus
 
Key Responsibilities  

Generative AI Development  
- Research, fine-tune, and deploy generative AI & LLM models for specific use cases.  
- Design and implement solutions for text generation, image synthesis, conversational AI, and more.  
- Optimize AI models for performance, scalability, and real-time applications.

Backend Development
- Build robust APIs and microservices to integrate AI models into web and mobile applications.  
- Develop efficient data pipelines for model training and inference.

Work with databases (SQL/NoSQL) Vector DB/Graph DB to handle structured and unstructured data
- Ensure backend systems are secure, scalable, and capable of handling AI workloads.  

Frontend Development
- Create intuitive user interfaces for applications powered by generative AI/ AI
- Collaborate with designers to bring AI-driven user experiences to life using frameworks like React, Angular, or Vue.  
- Implement dynamic visualizations or outputs generated by AI models.  
 

Cloud and Deployment
- Deploy AI models and full-stack applications on cloud platforms (AWS, Azure).  
- Implement