Description

Key Skills: Generative AI, Python, Pytorch, Cloud, LLM, Tensorflow

Roles and Responsibilities:

• Design, develop, and deploy scalable AI/ML and Generative AI solutions.
• Develop production-ready code using Python and relevant AI/ML frameworks.
• Build machine learning models for classification, prediction, forecasting, recommendation, anomaly detection, NLP, and document processing.
• Design and implement Generative AI solutions using Large Language Models.
• Develop Retrieval-Augmented Generation solutions using enterprise documents and data.
• Build AI agents, conversational assistants, document intelligence, and workflow automation solutions.
• Design end-to-end AI solution architecture covering applications, APIs, data, models, integrations, security, and cloud infrastructure.
• Develop APIs and microservices using FastAPI, Flask, or similar frameworks.
• Work with embeddings, vector databases, semantic search, hybrid search, and reranking techniques.
• Perform prompt engineering, model selection, grounding, fine-tuning, and LLM evaluation.
• Develop data ingestion, preprocessing, feature engineering, model training, testing, and inference pipelines.
• Establish MLOps and LLMOps pipelines for automated deployment, versioning, monitoring, and retraining.
• Monitor model accuracy, performance, drift, hallucination, latency, availability, and operating cost.
• Implement AI security controls and guardrails to prevent data leakage, prompt injection, harmful output, and unauthorized access.
• Apply Responsible AI principles, including fairness, transparency, explainability, privacy, safety, and accountability.
• Integrate AI solutions with enterprise applications, databases, APIs, cloud services, and third-party platforms.
• Design secure, scalable, resilient, and cost-effective cloud-based AI architecture.
• Prepare solution architecture diagrams, technical designs, data-flow diagrams, API specifications, and deployment documents.
• Conduct technical feasibility assessments, proofs of concept, and technology evaluations.
• Translate business requirements into AI use cases, technical requirements, and appropriate solution designs.
• Collaborate with product owners, business teams, data scientists, data engineers, cloud teams, security teams, and software developers.
• Review code and solution designs to ensure quality, security, scalability, and maintainability.
• Provide technical guidance and mentoring to AI/ML engineers and development teams.
• Support effort estimation, sprint planning, technical delivery, production deployment, and issue resolution.

Skills Required:

• Strong hands-on programming experience in Python.
• Experience with Scikit-learn, PyTorch, TensorFlow, XGBoost, Pandas, and NumPy.
• Hands-on experience with Generative AI, LLMs, embeddings, prompt engineering, and Retrieval-Augmented Generation.
• Experience with LangChain, LangGraph, Semantic Kernel, LlamaIndex, or similar frameworks.
• Experience with vector databases and search platforms such as Azure AI Search, Pinecone, Elasticsearch, Weaviate, Milvus, or pgvector.
• Strong understanding of machine learning algorithms, deep learning, NLP, model evaluation, and statistical techniques.
• Experience developing REST APIs, microservices, and event-driven integrations.
• Experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud.
• Knowledge of Docker, Kubernetes, CI/CD, Git, and infrastructure-as-code.
• Experience with MLOps platforms such as Azure Machine Learning, MLflow, Databricks, SageMaker, or Vertex AI.
• Strong knowledge of SQL, relational databases, NoSQL databases, data lakes, lakehouses, and data pipelines.
• Understanding of cloud security, identity management, encryption, access control, networking, and audit logging.
• Knowledge of AI governance, Responsible AI, data privacy, and model risk management.
• Ability to create and communicate high-level and low-level solution architecture.
• Strong analytical, problem-solving, stakeholder-management, and communication skills.

Education: Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, Engineering, or a related field

Key Skills

Education

Any Graduate