JobSummary:

We are seeking an experienced Generative & Agentic AI Developer with 7 years of IT experience including strong expertise in Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) and agent-based AI systems. This role focuses on developing and deploying advanced GenAI applications and autonomous Agentic AI workflows that enable intelligent automation reasoning and decision-making. The ideal candidate will have hands-on proficiency with Python AI/ML frameworks multi-agent orchestration platforms prompt engineering and cloud-native environments to ensure scalable secure and production-ready solutions.

InthisRoleYourResponsibilitiesWillBe:

• Design fine-tune and deploy advanced GenAI models (LLMs Diffusion GANs VAEs Transformers GNNs) for multimodal NLP and autonomous agentic applications.
• Engineer end-to-end RAG pipelines and multi-agent workflows using LangChain AutoGen Copilot MCP.
• Integrate vector DBs (PostreSQL Pinecone Weaviate Chroma FAISS Redis) and graph DBs (Neo4j Postgres/pgvector) for semantic retrieval and contextual reasoning.
• Optimize foundation models (GPT-4 LLaMA Mistral Falcon) via prompt engineering RLHF LoRA quantization and hyperparameter tuning.
• Build scalable AI solutions using Azure AI/ML (preferred) with containerized deployments (Docker Kubernetes).
• Apply MLOps best practices: CI/CD model versioning drift detection observability and lifecycle management with MLflow Kubeflow Airflow and monitoring tools.
• Develop secure AI pipelines and APIs with Python FastAPI/Flask RBAC OAuth2 JWT and encryption standards.
• Conduct model optimization: prompt engineering hyperparameter tuning cross-validation and performance monitoring.
• Use tools like Azure Machine Learning OpenAI API HuggingFace or custom PyTorch/TensorFlow-based models.
• Implement AI safety bias mitigation interpretability (SHAP LIME and compliance guardrails (GDPR HIPAA ISO).
• Collaborate with cross-functional teams to deliver enterprise-grade copilots assistants and reusable AI components.
• Document AI design model workflows and deployment pipelines for audit readiness and knowledge sharing.

• Build scalable AI applications using MLOps CICD containerization (Docker Kubernetes) and deploy on Azure AI Infrastructure (preferred) or AWS if needed.

• Bachelors or Masters degree in Computer Science Data Science Statistics Mathematics or a related field over 7 years.
• Proven experience as a Gen AI Developer or in a similar role and proficiency in Python
• Strong Experience with Agentic Solution Development RAG Deep Learning Prompt Engineering Natural Language Processing (NLP) computer vision optimization while maintaining performance techniques.
• Strong understanding and practical knowledge of LLMs embeddings RAG and Vector Search.
• Proficient in prompt engineering and conversational AI solution design.
• Experience with AI on Azure (must) including Azure OpenAI Azure ML and related services.
• Deep hands-on experience in Python CUDA SQL proficient with TensorFlow PyTorch Keras.
• Familiarity with security bias mitigation and responsible AI frameworks.
• Experience with MLOps practices and tools for deploying tracking and updating models.
• Knowledge of ML algorithms (e.g. CNNs RNNs SVMs Random Forests k-NN Naïve Bayes).
• Excellent problem-solving communication and team collaboration skills.

Qualifications:

Preferred Qualifications:

• Certifications in AI/ML from Microsoft AWS or Coursera/edX.
• Exposure to enterprise use cases in industries such as manufacturing finance and other.
• Experience with AutoML LLMOps and performance benchmarking tools.
• Understanding of semantic search knowledge graphs and contextual recommendation engines.

• Hands on MLOps experience with an appreciation of the end-to-end CI/CD process

• Certified inAzure AI Fundamentals (AI-900) Azure AI Engineer Associate (AI-102) Azure Developer Associate.

• Experience with big data technologies