AI/ML Engineer – Agentic AI & Generative AI

Role: Lead Angular DeveloperLocation: RemoteJob Type: Full-TimeExperience: 12+ YearsEligibility: H4 EAD / L2S / GC / USC / TN onlyNote: No C2C / No consultancy resumesPosition Overview: We are seeking a highly motivated AI/ML Engineer with expertise in Machine Learning, Statistics, Generative AI, and Agentic AI frameworks to design, develop, and deploy intelligent AI-powered solutions. The ideal candidate will possess a strong foundation in machine learning concepts, hands-on experience with Large Language Models (LLMs), and proven experience building production-grade Retrieval-Augmented Generation (RAG) and Agentic AI applications.Key ResponsibilitiesDesign, develop, and deploy scalable AI/ML solutions to address complex business challenges.Build and optimize Machine Learning models using industry-standard methodologies and evaluation techniques.Develop Agentic AI applications utilizing frameworks such as LangChain, AutoGen, and CrewAI.Design and implement Retrieval-Augmented Generation (RAG) pipelines using vector databases and embedding models.Integrate Large Language Models (LLMs) into enterprise applications and workflows.Evaluate model performance using appropriate metrics and continuously improve solution effectiveness.Collaborate with cross-functional teams to translate business requirements into AI-driven solutions.Ensure scalability, reliability, and performance of deployed AI systems.Required QualificationsBachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, or a related field.4+ years of experience in Machine Learning, Artificial Intelligence, or Data Science.Strong understanding of statistical concepts and machine learning algorithms.Proficiency in Python and related AI/ML libraries such as Scikit-Learn, Pandas, NumPy, TensorFlow, or PyTorch.Hands-on experience with Generative AI and Agentic AI frameworks, including:LangChainAutoGenCrewAIExperience building and deploying RAG-based solutions.Experience working with vector databases such as:PineconeChromaDBFAISSWeaviateMilvusStrong understanding of LLM architectures, prompt engineering, embeddings, and semantic search.Experience integrating OpenAI, Anthropic Claude, Gemini, Llama, or equivalent foundation models.Machine Learning & Statistics ExpertiseCandidates should demonstrate proficiency in:Supervised and Unsupervised Learning techniques.Model training, validation, and optimization.Feature Engineering and Data Preprocessing.Statistical Analysis and Hypothesis Testing.Model Evaluation Metrics, including:PrecisionRecallF1 ScoreROC-AUCAccuracyConfusion Matrix AnalysisPreferred QualificationsExperience with AWS, Azure, or Google Cloud Platform.Knowledge of MLOps, CI/CD pipelines, and model deployment strategies.Experience with AI monitoring, observability, and evaluation frameworks.Experience developing enterprise-scale AI solutions in production environments.Familiarity with API development and microservices architecture.Required Project ExperienceCandidates should be able to demonstrate at least one production implementation involving:Agentic AI or Multi-Agent Systems.Retrieval-Augmented Generation (RAG) Architecture.Vector Database Integration.LLM-Based Application Development.Quantifiable business outcomes, such as:Increased operational efficiencyProcess automationCost reductionImproved accuracy and response qualityEnhanced user productivity