Generative AI Engineer

Job Title: Generative AI Engineer
Company: ShrinQ Consulting Group Inc.
Employment Type: Full-Time (Fully Remote)
Experience Level: Mid-Level (3–7 Years)
Industry: Artificial Intelligence, Machine Learning, Software Engineering, Consulting
Key Responsibilities:
Design, develop, and deploy advanced Generative AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and cloud-native AI services.
Collaborate with data scientists, engineers, and product teams to build scalable, secure, and production-ready AI solutions.
Implement RAG pipelines with vector databases (e.g., Pinecone, ChromaDB).
Develop AI agents for multi-step reasoning, workflow automation, and tool integration.
Integrate foundation models via APIs and open-source frameworks (e.g., LangChain, LangGraph).
Fine-tune, evaluate, and optimize language models for business-specific applications.
Build secure RESTful APIs and backend services for AI applications.
Monitor model performance, latency, cost, and reliability in production.
Required Qualifications:
Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field.
3+ years of experience in software engineering, ML, or AI development.
Strong Python programming skills.
Experience with LLMs (e.g., OpenAI GPT, Llama, Mistral) and frameworks (LangChain, LangGraph).
Knowledge of RAG, embeddings, prompt engineering, and vector databases.
Experience with REST APIs (FastAPI, Flask, Django), Docker, Kubernetes, and CI/CD pipelines.
Preferred Qualifications:
Experience with AI orchestration platforms (e.g., MCP) and agent frameworks.
MLOps/LLMOps tools (MLflow, LangSmith, Weights & Biases).
Cloud AI platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI).
SQL, NoSQL, and graph databases.
Multimodal AI, computer vision, or open-source contributions.
Why Join Us:
Work on enterprise AI projects across diverse industries.
Access cutting-edge Generative AI technologies and cloud-native solutions.
Competitive salary and performance-based incentives.
Fully remote work with flexible collaboration.
Opportunities for continuous learning, certifications, and career growth.