Key Responsibilities :

- Design, develop, and deploy scalable AI and Machine Learning solutions for enterprise applications

- Build and optimize Generative AI applications leveraging Large Language Models (LLMs)

- Develop Retrieval-Augmented Generation (RAG) pipelines and AI-powered knowledge systems

- Fine-tune foundation models using techniques such as LoRA and parameter-efficient tuning methods

- Implement multi-agent AI workflows and autonomous agent architectures

- Perform data preprocessing, feature engineering, model training, validation, and evaluation

- Integrate AI solutions with enterprise applications, APIs, and cloud platforms

- Monitor, optimize, and maintain AI models in production environments

- Collaborate with product, engineering, and business teams to deliver AI-driven solutions

- Ensure AI solutions meet performance, scalability, security, and governance requirements

Required Skills & Experience :

- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field

- Proven experience building and deploying AI/ML solutions in production environments

- Strong programming skills in Python and/or Java

- Solid understanding of Machine Learning concepts including :

1. Supervised Learning

2. Unsupervised Learning

3. Reinforcement Learning

4. Deep Learning & Neural Networks

- Experience with data preprocessing, feature engineering, and model evaluation techniques

- Hands-on experience with :

1. Context Engineering

2. Fine-Tuning (LoRA and related techniques)

3. Retrieval-Augmented Generation (RAG)

4. Multi-Agent Architectures

5. Prompt Engineering

- Experience working with AI orchestration frameworks such as :

1. LangChain

2. LlamaIndex

3. Spring AI

4. AutoGen

5. CrewAI

6. LangFuse

- Experience with cloud-based AI platforms such as :

1. AWS Bedrock

2. AWS SageMaker

- Proficiency with Git and modern software development practices

Good to Have :

- Experience with vector databases and embeddings

- Exposure to Agentic AI systems and autonomous workflows

- Knowledge of MLOps, model monitoring, and CI/CD for AI

- Experience with Kubernetes, Docker, and cloud-native deployments

- Familiarity with AI governance, security, and responsible AI practices

Preferred Candidate Profile :

- Strong analytical and problem-solving skills

- Ability to design scalable AI architectures from concept to production

- Excellent communication and stakeholder management skills

- Passion for emerging AI technologies and continuous learning

- Experience working in Agile and cross-functional product teams