AI ML Engineer / Malvern PA (Onsite) - FTEAI ML Engineer / Malvern PA (Onsite) - FTE

Role: AI/ML Engineer – Generative AI & AWS Location: Malvern, PA – Onsite Job Type: Full-Time / Permanent Job Summary We are seeking an experienced AI/ML Engineer with strong expertise in Generative AI, Machine Learning, LLMs, and AWS cloud technologies. The ideal candidate will be responsible for designing, developing, deploying, and optimizing scalable AI/ML solutions using Amazon Bedrock, SageMaker, Python, RAG, AI Agents, and MLOps frameworks. The candidate will work closely with business, data engineering, and cloud teams to build secure, production-ready AI solutions that deliver measurable business value. Must-Have Technical Skills • Strong experience designing, developing, and deploying AI/ML and Generative AI solutions on AWS • Strong programming experience with Python, PySpark, and SQL • Hands-on experience with Machine Learning, Deep Learning, and NLP • Strong understanding of Generative AI, LLMs, Prompt Engineering, and LLM application development • Hands-on experience with Amazon Bedrock and AWS SageMaker • Strong experience building RAG (Retrieval-Augmented Generation) pipelines • Experience developing AI Agents / Agentic AI solutions • Hands-on experience with LangChain, LangGraph, and/or LlamaIndex • Strong knowledge of AWS services including: • Amazon S3 • AWS Lambda • IAM • Amazon RDS • CloudWatch • Experience with MLOps, MLflow, model lifecycle management, and CI/CD pipelines • Experience with Docker, Kubernetes, and Terraform • Strong experience developing and integrating REST APIs / FastAPI • Experience with model deployment, monitoring, performance tuning, and production support • Understanding of cloud-native architecture, security, scalability, and cost optimization Key Responsibilities • Design, develop, and deploy scalable AI/ML and Generative AI solutions using AWS services such as Amazon Bedrock, SageMaker, Lambda, and S3. • Build and optimize RAG pipelines, LLM-powered applications, AI Agents, and model inference workflows. • Develop data and ML pipelines to support model training, evaluation, deployment, monitoring, and continuous improvement. • Implement MLOps practices and automated CI/CD pipelines for reliable and repeatable model deployments. • Develop production-grade APIs and AI services using Python and FastAPI. • Integrate LLMs with enterprise data sources, vector databases, APIs, and business applications. • Evaluate and optimize model performance, latency, scalability, reliability, and cloud costs. • Implement appropriate security, IAM, monitoring, logging, and governance practices for AI workloads. • Containerize and deploy AI/ML applications using Docker and Kubernetes. • Collaborate with Data Engineers, Cloud Engineers, Architects, Product Owners, and business stakeholders to translate business requirements into scalable AI solutions. • Troubleshoot production issues and continuously improve AI/ML solutions based on performance and business requirements. • Stay current with emerging developments in Generative AI, LLMs, Agentic AI, AWS AI services, and MLOps. Leadership & Managerial Skills • Strong leadership, communication, and stakeholder management skills. • Ability to work effectively with cross-functional and distributed teams. • Strong analytical and problem-solving abilities with a focus on delivering business outcomes. • Ability to communicate complex AI/ML concepts clearly to both technical and non-technical stakeholders. • Demonstrated ownership of projects from solution design through production deployment and support. • Strong focus on delivery excellence, quality, security, and continuous improvement. Preferred Qualifications • Experience with enterprise Generative AI implementations in production environments. • Experience with vector databases, embeddings, semantic search, and knowledge bases. • Experience with LLM evaluation, observability, guardrails, and responsible AI practices. • AWS certifications such as AWS Machine Learning Engineer, AWS Solutions Architect, or equivalent are a plus. • Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field.