Job Description:

Senior AI/ML Engineer

Job Title: Senior AI/ML Engineer
Experience: 12+ Years
Employment Type:  W2

Job Summary

We are seeking an experienced Senior AI/ML Engineer with 12+ years of experience in software engineering, machine learning, artificial intelligence, and advanced analytics. The ideal candidate will have strong expertise in Python, machine learning frameworks, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and cloud-based AI solutions.

The candidate will be responsible for designing, developing, deploying, and optimizing scalable AI/ML solutions that solve complex business problems.

Key Responsibilities

• Design, develop, and deploy machine learning and deep learning models for enterprise applications.
• Build and implement Generative AI solutions using LLMs, prompt engineering, and RAG architectures.
• Develop AI-powered applications using frameworks such as LangChain, LangGraph, and LlamaIndex.
• Work with OpenAI, Azure OpenAI, AWS Bedrock, or Google Vertex AI to build intelligent applications.
• Develop and optimize NLP, predictive analytics, classification, regression, and recommendation models.
• Build data pipelines and prepare large datasets for training, validation, and inference.
• Implement vector databases and semantic search solutions using Pinecone, FAISS, ChromaDB, or similar technologies.
• Deploy AI/ML models using Docker, Kubernetes, REST APIs, and CI/CD pipelines.
• Implement model monitoring, performance optimization, and MLOps practices.
• Collaborate with data engineers, software developers, architects, and business stakeholders.
• Ensure AI solutions meet security, scalability, governance, and responsible AI requirements.
• Mentor junior engineers and contribute to technical architecture and design decisions.

Required Technical Skills

• Programming: Python, SQL, REST APIs
• Machine Learning: Scikit-learn, TensorFlow, PyTorch, XGBoost
• Generative AI: LLMs, RAG, prompt engineering, AI agents
• AI Frameworks: LangChain, LangGraph, LlamaIndex
• Cloud Platforms: AWS, Azure, or Google Cloud Platform
• Vector Databases: Pinecone, FAISS, ChromaDB, or equivalent
• Data Processing: Pandas, NumPy, Spark, ETL/ELT
• MLOps: MLflow, model deployment, monitoring, CI/CD
• DevOps: Docker, Kubernetes, Git, automated deployment pipelines
• Strong knowledge of model evaluation, optimization, and production deployment.

Preferred Qualifications

• Experience building Agentic AI and multi-agent systems.
• Knowledge of AI orchestration, tool calling, and function calling.
• Experience with fine-tuning, embeddings, and transformer architectures.
• Familiarity with Snowflake, Databricks, and cloud data platforms.
• Experience implementing AI governance, guardrails, and evaluation frameworks.
• Strong communication, problem-solving, and technical leadership skills.