AI/ML Software Engineer (Generative AI & LLMs)

avanciers inc. • United State
Remote
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AI Summary

Design, develop, and deploy enterprise-scale Machine Learning and Generative AI solutions. The ideal candidate will have strong expertise in Python, LLMs, NLP, MLOps, cloud platforms, and production-grade AI systems. This is a hands-on engineering role that combines technical leadership, solution architecture, and end-to-end ownership of AI applications.

Key Highlights
Design, develop, and deploy scalable AI/ML, LLM, and Generative AI solutions
Build and optimize Retrieval-Augmented Generation (RAG) pipelines and intelligent NLP applications
Implement MLOps practices including model deployment, monitoring, automation, and lifecycle management
Key Responsibilities
Design, develop, and deploy scalable AI/ML, LLM, and Generative AI solutions
Build and optimize Retrieval-Augmented Generation (RAG) pipelines and intelligent NLP applications
Implement MLOps practices including model deployment, monitoring, automation, and lifecycle management
Technical Skills Required
Python OpenAI APIs LLMs TensorFlow PyTorch Scikit-learn AWS Azure GCP Docker Kubernetes CI/CD Microservices architecture MLOps
Benefits & Perks
100% remote
Contract (C2C/W2)/ Full-Time
Nice to Have
Experience in financial services, banking, or fintech domains
Knowledge of vector databases such as Pinecone, Weaviate, ChromaDB, or FAISS
Experience with LangChain, LlamaIndex, and AI orchestration frameworks

Job Description


Avanciers is a premier IT Staffing & Consulting organization and we are currently recruiting for a Full-Time opportunity with one of our premier clients in USA.


Job Title: AI/ML Software Engineer (Generative AI & LLMs)

Location: 100% Remote

Employment Type: Contract (C2C/ W2)/ Full-Time

Experience Required: 8–15 Years


About the Role

We are seeking an experienced AI/ML Software Engineer to design, develop, and deploy enterprise-scale Machine Learning and Generative AI solutions. The ideal candidate will have strong expertise in Python, LLMs, NLP, MLOps, cloud platforms, and production-grade AI systems. This is a hands-on engineering role that combines technical leadership, solution architecture, and end-to-end ownership of AI applications.

Key Responsibilities

  • Design, develop, and deploy scalable AI/ML, LLM, and Generative AI solutions from concept to production.
  • Build and optimize Retrieval-Augmented Generation (RAG) pipelines and intelligent NLP applications.
  • Develop and integrate AI services using OpenAI APIs and modern LLM frameworks.
  • Implement MLOps practices including model deployment, monitoring, automation, and lifecycle management.
  • Fine-tune and evaluate generative AI models to improve performance, accuracy, and reliability.
  • Build cloud-native AI applications using microservices, containers, and orchestration platforms.
  • Collaborate with product managers, data scientists, and cross-functional teams to deliver business-driven AI solutions.
  • Conduct architecture reviews, code reviews, and mentor junior engineers.
  • Monitor model performance and implement continuous improvements for production environments.
  • Communicate technical concepts and AI capabilities effectively to both technical and business stakeholders.

Required Skills

  • 8–15 years of software engineering experience with 3+ years in AI/ML and Generative AI.
  • Strong programming skills in Python.
  • Hands-on experience with OpenAI APIs, LLMs, and prompt engineering.
  • Experience with TensorFlow, PyTorch, Scikit-learn, or similar ML frameworks.
  • Strong understanding of machine learning, deep learning, NLP, and model evaluation techniques.
  • Experience building and deploying RAG-based applications.
  • Expertise with cloud platforms such as AWS, Azure, or GCP.
  • Experience with Docker, Kubernetes, CI/CD, and microservices architecture.
  • Knowledge of MLOps, model monitoring, governance, and production operations.
  • Excellent communication, collaboration, and problem-solving skills.

Preferred Qualifications

  • Experience in financial services, banking, or fintech domains.
  • Knowledge of vector databases such as Pinecone, Weaviate, ChromaDB, or FAISS.
  • Experience with LangChain, LlamaIndex, and AI orchestration frameworks.
  • Familiarity with Chain-of-Thought (CoT), Tree-of-Thought (ToT), and Graph-of-Thought (GoT) prompting techniques.
  • Experience leading technical teams and mentoring engineers.

Education

  • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.

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