Gen AI Engineer

Cynosure Corporate Solutions; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Cynosure Corporate Solutions is seeking skilled Gen AI Engineers and Leads to design, build, and scale enterprise GenAI and Agentic AI solutions. You will work on multimodal applications, GenAI pipelines, and LLM orchestration across cloud platforms.

The role requires hands-on experience with LangChain, LlamaIndex, and modern AI frameworks, plus deployment on AWS/Azure/GCP. Office presence is required five days a week.

Qualifications

• Bachelor's or Master's in CS/AI/related field.
• 4–8 years in GenAI/ML or software engineering.
• Hands-on GenAI and Agentic AI development experience.
• Proficient in Python and modern AI frameworks.
• Experience with LangChain, LlamaIndex, or similar.

Responsibilities

• Design, develop, and deploy GenAI/Agentic AI applications.
• Build multimodal AI solutions for enterprise use cases.
• Develop GenAI pipelines: data prep, training, eval, deployment.
• Implement LLM orchestration using LangChain, LlamaIndex, HuggingFace, OpenAI APIs.
• Develop RAG systems with embeddings, cross-encoders, hybrid search.
• Manage vector databases: Pinecone, Weaviate, ChromaDB, FAISS, Milvus.
• Implement MLOps/LLMOps: CI/CD, monitoring, testing, drift detection.
• Prompt engineering and parameter-efficient tuning (LoRA/QLoRA).
• Integrate AI models with enterprise systems via REST APIs, GraphQL, Kafka.
• Deploy AI workloads on AWS/Azure/GCP using Docker, Kubernetes, serverless.
• Collaborate with cross-functional teams for scalable, production-ready solutions.

Skills

GenAI development

Agentic AI

Python

LLMs

LangChain

RAG architectures

Vector databases

MLOps

CI/CD

Docker

Kubernetes

Cloud platforms

REST APIs

GraphQL

Microservices

AWS/Azure/GCP

Education

Bachelor's or Master's in CS/AI/Data Science

Tools

LangChain

LlamaIndex

Hugging Face Transformers

AutoGen

OpenAI APIs

Pinecone

Weaviate

ChromaDB

FAISS

Milvus

Kafka

REST APIs

GraphQL

Job description

We are looking for skilled Gen AI / Agentic AI Engineers and Leads to join our growing AI team. The ideal candidate will have hands-on experience in building, deploying, and scaling Generative AI and Agentic AI solutions using modern LLM frameworks, vector databases, cloud platforms, and MLOps practices. The role involves developing enterprise-grade AI applications, intelligent automation systems, and scalable AI architectures.

Key Responsibilities:

• Design, develop, and deploy Generative AI and Agentic AI applications for enterprise use cases.
• Build multimodal AI solutions involving text, image, and document processing.
• Develop and optimize GenAI pipelines, including data preprocessing, model training, evaluation, and deployment.
• Implement LLM orchestration using LangChain, LlamaIndex, Hugging Face Transformers, AutoGen, and OpenAI APIs.
• Develop Retrieval-Augmented Generation (RAG) systems with efficient chunking, embeddings, cross-encoders, and hybrid search techniques.
• Manage and optimize vector databases such as Pinecone, Weaviate, ChromaDB, FAISS, and Milvus.
• Implement MLOps and LLMOps practices, including CI/CD pipelines, model monitoring, automated testing, and drift detection.
• Work on prompt engineering and parameter-efficient fine-tuning techniques such as LoRA and QLoRA.
• Integrate AI models with enterprise systems using REST APIs, GraphQL, Kafka, and microservices architecture.
• Deploy AI workloads across AWS, Azure, or GCP using Docker, Kubernetes, and serverless technologies.
• Collaborate with cross-functional teams to develop scalable and production-ready AI solutions.

Required Skills & Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
• 4-8 years of experience in Generative AI, Machine Learning, Software Engineering, or related domains.
• Strong hands-on experience in Generative AI and Agentic AI development.
• Proficiency in Python and modern AI/ML frameworks.
• Strong knowledge of LLMs, RAG architectures, Vector Databases, and Prompt Engineering.
• Experience with LangChain, LlamaIndex, Hugging Face, AutoGen, or similar frameworks.
• Experience deploying AI solutions on AWS, Azure, or GCP.
• Knowledge of scalable AI architecture, enterprise integrations, and microservices.
• Familiarity with MLOps, LLMOps, CI/CD, Docker, and Kubernetes.
• Strong problem-solving, analytical, and communication skills.
• Willingness to work from office 5 days a week.