Senior AI Engineer
Senior AI Engineer
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Job Description
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.
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
