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Job Description
Job Title:
Senior Generative AI Engineer Experience:
12+
Years Location:
[Remote/Hybrid/Onsite]
Employment Type:
W2 Position Overview We are seeking a highly experienced Senior Generative AI Engineer with 12+ years of overall software engineering experience and deep expertise in designing, developing, and deploying enterprise-scale AI/ML and Generative AI solutions. The ideal candidate will have strong hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, model fine-tuning, vector databases, and cloud-native AI platforms. This role requires a combination of software engineering excellence, AI/ML expertise, solution architecture skills, and the ability to lead GenAI initiatives from concept to production. Key Responsibilities Generative AI Development Design, develop, and deploy enterprise-grade Generative AI applications using state-of-the-art LLMs. Build and optimize RAG (Retrieval-Augmented Generation) architectures for knowledge-intensive applications. Develop AI-powered chatbots, virtual assistants, copilots, and intelligent automation solutions. Design and implement multi-agent AI systems and agentic workflows. Perform prompt engineering, model evaluation, and response optimization. Fine-tune and customize foundation models for domain-specific use cases. AI/ML Engineering Build end-to-end machine learning and GenAI pipelines. Develop model training, validation, deployment, and monitoring frameworks. Implement MLOps and LLMOps best practices. Create automated evaluation systems for LLM performance, safety, and accuracy. Work with structured, semi-structured, and unstructured data sources. Architecture & Solution Design Architect scalable AI platforms capable of supporting enterprise workloads. Design microservices-based AI applications using cloud-native technologies. Integrate GenAI solutions with enterprise applications, APIs, databases, and business workflows. Establish AI governance, security, and compliance standards. Leadership & Collaboration Lead technical design discussions and architecture reviews. Mentor AI engineers, data scientists, and software developers. Collaborate with business stakeholders to identify AI opportunities and define solution roadmaps. Drive innovation and evaluate emerging AI technologies and frameworks. Required Qualifications Experience 12+ years of overall software engineering experience. 5+ years of AI/ML development experience. 3+ years of hands-on Generative AI implementation experience. Proven experience delivering production-grade GenAI solutions at enterprise scale. Programming & Development Expert-level proficiency in: Python REST APIs Microservices Architecture Object-Oriented Design Experience with: FastAPI Flask Async Programming Docker Kubernetes Generative AI Technologies Strong hands-on experience with: OpenAI GPT Models Claude Llama Models Gemini Mistral Prompt Engineering Function Calling AI Agents Multi-Agent Systems Tool Usage Frameworks GenAI Frameworks Experience with: LangChain LangGraph LlamaIndex CrewAI AutoGen Semantic Kernel Retrieval & Vector Search Experience implementing: RAG Architectures Hybrid Search Semantic Search Knowledge Graphs Vector databases: Pinecone Weaviate Chroma
DB FAISS
Milvus Elasticsearch/OpenSearch AI/ML Frameworks Strong experience with: PyTorch TensorFlow Scikit-learn Hugging Face Transformers PEFT LoRA Fine-Tuning Techniques MLOps / LLMOps Hands-on experience with: MLflow Kubeflow SageMaker Model Monitoring Model Registry CI/CD for AI Systems Experiment Tracking Cloud Platforms Experience with at least one: Amazon Web Services (AWS) Microsoft Azure Google Cloud Services such as: AI/ML Services Vector Search Services Serverless Computing Container Platforms Databases Experience with: PostgreSQL MySQL MongoDB Redis Neo4j Vector Databases Preferred Qualifications Experience building AI solutions in Financial Services, Healthcare, Insurance, Retail, or Technology domains. Experience with Responsible AI and AI Governance frameworks. Knowledge of AI security, model explainability, and compliance requirements. Experience with Knowledge Graphs and Graph Databases. Experience integrating GenAI with enterprise platforms such as Salesforce, ServiceNow, SAP, or Workday. Exposure to multimodal AI applications involving text, images, audio, and video. Education Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field. Advanced AI/ML certifications preferred.
Nice-to-Have Certifications AWS Certified Machine Learning Specialty Azure AI Engineer Associate Google Professional Machine Learning Engineer Databricks Machine Learning Professional Generative AI Professional Certifications Key Skills Summary Generative AI:
PyTorch, TensorFlow, Scikit-learn, Hugging Face LLMOps/MLOps:
MLflow, Kubeflow, CI/CD, Monitoring Cloud:
AWS, Azure, Google Cloud Platform Databases:
PostgreSQL, MongoDB, Redis, Neo4j,
Pinecone, Weaviate, FAISS Architecture:
Distributed Systems, Cloud-Native Design, Enterprise AI Platforms This role is ideal for a senior technologist who can lead the design and implementation of cutting-edge Generative AI solutions while driving enterprise AI transformation initiatives.
