Sr. Gen AI Developer
4 days ago
Job Summary: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. In this Role, Your Responsibilities Will Be:
- 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.
- Bachelor's or Master's 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 in Azure AI Fundamentals (AI-900), Azure AI Engineer Associate (AI-102), Azure Developer Associate.
Experience with big data technologies
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