Company Description
Quantanite is a customer experience (CX)solutions company that helpsfast-growing companiesand leading global brandsto transformand grow. We do thisthrough a collaborative andconsultative approach,rethinking business processes and ensuring our clients employ theoptimalmix of automationand human intelligence.We are an ambitiousteamof professionalsspread acrossfour continents and looking to disrupt ourindustry by delivering seamlesscustomerexperiencesforour clients,backed-upwithexceptionalresults.We havebig dreams,and are constantly looking for new colleaguesto join us who share our values, passion andappreciationfordiversity.
About the Role:
We are seeking a highly skilled Senior AI Engineer with deep expertise in Agentic frameworks, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, MLOps/LLMOps, and end-to-end GenAI application development. In this role, you will design, develop, fine-tune, deploy, and optimize state-of-the-art AI solutions across diverse enterprise use cases including AI Copilots, Summarization, Enterprise Search, and Intelligent Tool Orchestration.
Key Responsibilities:
- Develop and Fine-Tune LLMs (e.g., GPT-4, Claude, LLaMA, Mistral, Gemini) using instruction tuning, prompt engineering, chain-of-thought prompting, and fine-tuning techniques.
- Build RAG Pipelines: Implement Retrieval-Augmented Generation solutions leveraging embeddings, chunking strategies, and vector databases like FAISS, Pinecone, Weaviate, and Qdrant.
- Implement and Orchestrate Agents: Utilize frameworks like MCP, OpenAI Agent SDK, LangChain, LlamaIndex, Haystack, and DSPy to build dynamic multi-agent systems and serverless GenAI applications.
- Deploy Models at Scale: Manage model deployment using HuggingFace, Azure Web Apps, vLLM, and Ollama, including handling local models with GGUF, LoRA/QLoRA, PEFT, and Quantization methods.
- Integrate APIs: Seamlessly integrate with APIs from OpenAI, Anthropic, Cohere, Azure, and other GenAI providers.
- Ensure Security and Compliance: Implement guardrails, perform PII redaction, ensure secure deployments, and monitor model performance using advanced observability tools.
- Optimize and Monitor: Lead LLMOps practices focusing on performance monitoring, cost optimization, and model evaluation.
- Work with AWS Services: Hands-on usage of AWS Bedrock, SageMaker, S3, Lambda, API Gateway, IAM, CloudWatch, and serverless computing to deploy and manage scalable AI solutions.
- Contribute to Use Cases: Develop AI-driven solutions like AI copilots, enterprise search engines, summarizers, and intelligent function-calling systems.
- Cross-functional Collaboration: Work closely with product, data, and DevOps teams to deliver scalable and secure AI products.
Qualifications
Required Skills and Experience:
- 3-5 years of experience in AI/ML roles, focusing on LLM agent development, data science workflows, and system deployment.
- Demonstrated experience in designing domain-specific AI systems and integrating structured/unstructured data into AI models.
- Proficiency in designing scalable solutions using LangChain and vector databases.
- Deep knowledge of LLMs and foundational models (GPT-4, Claude, Mistral, LLaMA, Gemini).
- Strong expertise in Prompt Engineering, Chain-of-Thought reasoning, and Fine-Tuning methods.
- Proven experience building RAG pipelines and working with modern vector stores (FAISS, Pinecone, Weaviate, Qdrant).
- Hands-on proficiency in LangChain, LlamaIndex, Haystack, and DSPy frameworks.
- Model deployment skills using HuggingFace, vLLM, Ollama, and handling LoRA/QLoRA, PEFT, GGUF models.
- Practical experience with AWS serverless services: Lambda, S3, API Gateway, IAM, CloudWatch.
- Strong coding ability in Python or similar programming languages.
- Experience with MLOps/LLMOps for monitoring, evaluation, and cost management.
- Familiarity with security standards: guardrails, PII protection, secure API interactions.
- Use Case Delivery Experience: Proven record of delivering AI Copilots, Summarization engines, or Enterprise GenAI applications.
Additional Information
Preferred Skills:
- Experience in BPO or IT Outsourcing environments.
- Knowledge of workforce management tools and CRM integrations.
- Hands-on experience with AI technologies and their applications in data analytics.
- Familiarity with Agile/Scrum methodologies.
Soft Skills:
- Strong analytical and problem-solving capabilities.
- Excellent communication and stakeholder management skills.
- Ability to thrive in a fast-paced, dynamic environment.
