Sr. Gen AI Developer

• 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, Na ve 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 in Azure AI Fundamentals (AI-900), Azure AI Engineer Associate (AI-102), Azure Developer Associate.

• Experience with big data technologies