AI/ML Engineer (Generative AI, Agentic AI & AWS AI Platforms) | Tekishub Consulting Services | Malvern, PA / Dallas, TX / Charlotte, NC, USA

Job Title: AI/ML Engineer (Generative AI, Agentic AI & AWS AI Platforms) | Tekishub Consulting Services | Malvern, PA / Dallas, TX / Charlotte, NC, USA

Recruiting Company: Tekishub Consulting Services

Job Location: Malvern, Pennsylvania | Dallas, Texas | Charlotte, North Carolina (USA)

Job Type: Contract (6 Months)

Application Method

• Send your updated resume to
• Duration: 6 Months
• Work Mode: 100% Onsite
• Locations: Malvern, PA | Dallas, TX | Charlotte, NC
• Two Rounds of In-Person Interviews Mandatory
• Immediate Hiring Requirement

Position Summary

Tekishub Consulting Services is seeking an experienced AI/ML Engineer to design, develop, and deploy next-generation Artificial Intelligence solutions leveraging Generative AI, Agentic AI, and Large Language Models (LLMs). This role is ideal for candidates with strong expertise in AWS AI services, modern AI frameworks, and production-grade machine learning systems.

Detailed Job Description

As an AI/ML Engineer, you will be responsible for building enterprise-scale AI solutions that leverage Large Language Models, Agentic AI architectures, vector search, and advanced machine learning techniques. You will work closely with business stakeholders, data engineers, cloud architects, and software development teams to design intelligent applications that solve complex business challenges. The role requires hands-on expertise in Generative AI development, LLM orchestration, model deployment, cloud-native AI platforms, and scalable MLOps practices. Successful candidates will contribute to the end-to-end AI lifecycle, from data preparation and model development to deployment, monitoring, and continuous optimization. This is an excellent opportunity to work on cutting-edge AI initiatives within a highly innovative environment.

Key Responsibilities

• Design, develop, and deploy enterprise AI and Machine Learning solutions.
• Build and optimize Generative AI and Agentic AI applications using modern LLM technologies.
• Develop Retrieval-Augmented Generation (RAG) architectures and intelligent knowledge retrieval systems.
• Implement AI orchestration workflows using LangChain, LangGraph, and related frameworks.
• Build scalable AI services, APIs, and backend components for enterprise applications.
• Fine-tune, evaluate, and optimize machine learning and foundation models.
• Develop AI solutions utilizing Amazon Bedrock, SageMaker, and AWS AI services.
• Design and manage vector database and semantic search implementations.
• Collaborate with cloud, data engineering, and application development teams to deliver production-ready AI systems.
• Monitor AI model performance, reliability, security, and operational efficiency.
• Implement best practices for MLOps, CI/CD, model governance, and AI lifecycle management.
• Prepare technical documentation, architecture designs, and implementation guidelines.

Required Qualifications & Skills

• Bachelor’s or Master’s Degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
• Strong experience in Artificial Intelligence and Machine Learning engineering.
• Hands-on expertise with Large Language Models (LLMs) and Generative AI solutions.
• Experience designing and implementing Agentic AI architectures and intelligent AI workflows.
• Strong proficiency in Python programming.
• Experience with AWS AI services, including Amazon Bedrock and Amazon SageMaker.
• Hands-on experience with LangChain and LangGraph frameworks.
• Strong knowledge of machine learning algorithms, model development, and deployment methodologies.
• Experience building APIs, AI services, and scalable backend systems.
• Understanding of vector embeddings, semantic search, and retrieval systems.
• Knowledge of MLOps, cloud-native architectures, and production AI environments.
• Strong analytical, troubleshooting, and problem-solving capabilities.
• Excellent communication and stakeholder engagement skills.

Nice-to-Have Skills

• Experience with Claude, OpenAI, Gemini, or other frontier AI models.
• Knowledge of vector databases such as Pinecone, Weaviate, Chroma, or FAISS.
• Experience with Kubernetes, Docker, and cloud-native deployment environments.
• Familiarity with TensorFlow, PyTorch, and deep learning frameworks.
• Experience building enterprise AI copilots, intelligent assistants, and automation solutions.

Recruitment Pro Tip

For AI/ML Engineer roles, recruiters prioritize candidates who can demonstrate real-world implementations of Generative AI, Agentic AI, LLMs, Amazon Bedrock, SageMaker, LangChain, LangGraph, RAG, Vector Databases, AI Agents, Prompt Engineering, and Production AI Deployments. Include measurable outcomes such as accuracy improvements, automation benefits, latency reductions, cost savings, or successful enterprise AI implementations to significantly strengthen your application.