Apexon
AI

AI ML Engineer – LLM Conversational AI MCP

Apexon · · $12k

Actively hiring Posted about 1 month ago

Role overview

Direct message the job poster from Apexon

Sanjana Bisht

Sanjana Bisht

Executive II - Talent Acquisition at Apexon | Technical & Diversity Recruiting

Job Title: AI/ML Engineer – LLM & Conversational AI (MCP)
Location: Remote
Employment Type: Full-time

🚀 About the Role
We are looking for an experienced AI/ML Engineer with deep expertise in Large Language Models (LLMs), Conversational AI, and Model Context Protocol (MCP). In this role, you will design, build, and optimize intelligent AI systems that power chatbots, copilots, and enterprise-grade AI solutions.
You will work closely with product, UX, and engineering teams to transform business needs into scalable, secure, and high-performing AI applications.

🔧 Key Responsibilities

Design, develop, and deploy AI/ML solutions with a focus on LLMs and Generative AI

Build and optimize Conversational AI systems (chatbots, virtual assistants, AI agents)
Implement prompt engineering, fine-tuning, RAG (Retrieval-Augmented Generation), and evaluation pipelines
Develop and integrate MCP-based architectures for:
Context management
Tool calling
Memory handling
Agent orchestration
Work with vector databases such as Pinecone, FAISS, Weaviate, or Chroma
Integrate LLMs with enterprise systems, APIs, and third-party tools

Ensure model performance, scalability, security, and responsible AI usage

Monitor, test, and continuously improve model accuracy and response quality
Collaborate cross-functionally to deliver production-ready AI solutions

  • Required Skills & Qualifications

Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow)
Hands-on experience with LLMs (OpenAI, Azure OpenAI, Anthropic, Google Gemini, or open-source models)
Experience with Conversational AI frameworks such as LangChain, LlamaIndex, or Semantic Kernel

Solid understanding of Model Context Protocol (MCP) concepts
Strong knowledge of NLP, embeddings, and semantic search

Experience with cloud platforms (AWS, Azure, or GCP)
Familiarity with REST APIs, microservices, Docker, and Kubernetes

🌟 Nice to Have

Experience with multi-agent systems

Knowledge of speech-to-text / text-to-speech pipelines
Exposure to MLOps tools (MLflow, Kubeflow, CI/CD for ML)
Experience in Healthcare, FinTech, or enterprise AI solutions

Understanding of AI governance, privacy, and compliance

🎓 Education

Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or a related field
Equivalent practical experience is welcome

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Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Engineering and Information Technology

Industries

IT Services and IT Consulting

Tags & focus areas

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