- Hiring from
- United States
- Work type
- Remote
- Posted
- Sep 28, 2026
About the Role
We are seeking a highly skilled AI Engineer to design, develop, and deploy cutting-edge Artificial Intelligence solutions utilizing Generative AI, Agentic AI, Large Language Models (LLMs), NLP, and modern Data Engineering practices. The ideal candidate will possess strong expertise in building scalable AI applications, developing intelligent agents, integrating foundation models such as Claude, OpenAI GPT, Llama, Mistral, and other open-source or commercial LLMs, and engineering production-grade AI platforms.
Job Description (JD) – AI Engineer Position Title
AI Engineer
Experience
9-12 Years
Location
Remote
Employment Type
Full-Time
About the Role
We are seeking a highly skilled AI Engineer to design, develop, and deploy cutting-edge Artificial Intelligence solutions utilizing Generative AI, Agentic AI, Large Language Models (LLMs), NLP, and modern Data Engineering practices. The ideal candidate will possess strong expertise in building scalable AI applications, developing intelligent agents, integrating foundation models such as Claude, OpenAI GPT, Llama, Mistral, and other open-source or commercial LLMs, and engineering production-grade AI platforms.
Key Responsibilities
- Design, develop, and deploy AI/ML and Generative AI solutions for enterprise-scale applications.
- Build and optimize AI-powered applications leveraging LLMs, Agentic AI frameworks, and NLP techniques.
- Develop intelligent multi-agent systems for automation, reasoning, workflow orchestration, and decision-making.
- Implement Retrieval-Augmented Generation (RAG) architectures using vector databases.
- Fine-tune, evaluate, and deploy open-source and commercial LLMs.
- Develop scalable data ingestion, transformation, and feature engineering pipelines for AI workloads.
- Create conversational AI applications, virtual assistants, copilots, and knowledge management solutions.
- Integrate AI applications with enterprise systems through APIs, microservices, and cloud-native architectures.
- Monitor, evaluate, and continuously improve model performance, accuracy, safety, and governance.
- Collaborate with Data Engineers, Data Scientists, Product Managers, and Business Stakeholders to deliver AI-driven solutions.
Required Technical Skills Data Engineering
- Strong expertise in Python and SQL.
- Experience with ETL/ELT pipelines and data processing frameworks.
- Hands-on experience with Databricks, Spark/PySpark, Azure Data Factory, or equivalent data platforms.
- Knowledge of data modeling, data lakes, lakehouses, and data warehousing concepts.
- Experience with cloud platforms such as Azure, AWS, or GCP.
Generative AI
- Hands-on experience building GenAI applications using:
- OpenAI GPT Models
- Claude
- Llama
- Mistral
- Gemini
- Other open-source foundation models
- Experience with:
- Prompt Engineering
- Fine-Tuning
- RAG (Retrieval-Augmented Generation)
- Semantic Search
- Vector Embeddings
Agentic AI
- Experience developing AI Agents using:
- LangChain
- LangGraph
- CrewAI
- AutoGen
- Semantic Kernel
- Knowledge of:
- Multi-Agent Architectures
- Agent Orchestration
- Autonomous Workflows
- Tool Calling & Function Calling
- AI Planning & Reasoning Systems
NLP (Natural Language Processing)
- Strong understanding of:
- Text Classification
- Named Entity Recognition (NER)
- Topic Modeling
- Sentiment Analysis
- Text Summarization
- Document Intelligence
- Information Extraction
- Experience with:
- Hugging Face
- spaCy
- NLTK
- Transformers
LLMs (Open Source & Commercial)
- Hands-on experience with:
- Claude
- GPT-4/GPT-4o
- Llama 2/3
- Mistral
- Gemini
- Falcon
- Experience in:
- Model Evaluation
- Fine-Tuning
- Quantization
- Model Optimization
- Prompt Engineering
- LLMOps
Preferred Skills
- Experience with Vector Databases:
- Pinecone
- ChromaDB
- FAISS
- Weaviate
- Azure AI Search
- Knowledge of MLOps/LLMOps:
- MLflow
- Azure ML
- Kubeflow
- Docker
- Kubernetes
- Experience with REST APIs, FastAPI, Flask.
- Familiarity with Responsible AI, AI Governance, and Security practices.
- Exposure to Knowledge Graphs and Graph RAG.
Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or related fields.
- 7+ years of experience in Data Engineering, AI/ML, or related domains.
- Proven experience delivering production-grade Generative AI and Agentic AI solutions.
Key Competencies
- Strong problem-solving and analytical skills.
- Excellent communication and stakeholder management skills.
- Ability to translate business requirements into AI-driven solutions.
- Strong understanding of AI architecture, scalability, governance, and security.
- Hands-on mindset with the ability to rapidly prototype and productionize AI applications.
Nice to Have
- Microsoft Azure AI Engineer Associate Certification
- Databricks Certified Data Engineer
- AWS Certified Machine Learning Specialty
- Experience with enterprise copilots and AI assistants
- Experience working in regulated industries such as Banking, Healthcare, or Insurance
Collaborate with cross functional teams to understand requirements and translate them into effective AI system architectures.
Support the implementation of AI infrastructure projects, ensuring they are completed on time and within budget.
Maintain and improve existing AI infrastructure, addressing any issues that arise and implementing enhancements. Bachelor Degree 6 to 7 Years