Senior AI Engineer

## Position Overview

We are seeking a highly skilled Senior AI Engineer to join our team and drive the development of cutting-edge AI solutions. The ideal candidate will have extensive experience in Python development, deep expertise in Retrieval-Augmented Generation (RAG) systems, and a proven track record of deploying AI applications at scale.

## Key Responsibilities

### AI System Development

- Design, develop, and optimize RAG (Retrieval-Augmented Generation) systems for enterprise applications

- Build and maintain vector databases and embedding pipelines for efficient document retrieval

- Implement advanced prompt engineering techniques and fine-tuning strategies for large language models

- Develop multi-modal AI systems integrating text, image, and other data types

### Technical Architecture & Implementation

- Lead the architecture and implementation of scalable AI infrastructure using Python

- Design and implement robust data preprocessing pipelines for various AI models

- Optimize model performance through efficient inference techniques and caching strategies

- Develop APIs and microservices for AI model deployment and integration

### MLOps & Deployment

- Build and maintain CI/CD pipelines for AI model deployment using tools like Docker, Kubernetes, and cloud platforms

- Implement monitoring, logging, and observability solutions for production AI systems

- Manage model versioning, A/B testing, and rollback strategies

- Ensure security best practices in AI system deployment and data handling

### Research & Innovation

- Stay current with the latest developments in AI/ML research and emerging technologies

- Evaluate and integrate new AI frameworks, libraries, and tools into existing systems

- Collaborate with research teams to prototype and validate new AI approaches

- Contribute to technical documentation and knowledge sharing across the organization

## Required Qualifications

### Technical Skills

- *Programming*: 5+ years of professional Python development experience with expertise in libraries such as:

- PyTorch, TensorFlow, or similar deep learning frameworks

- LangChain, LlamaIndex, or similar RAG frameworks

- NumPy, Pandas, Scikit-learn for data manipulation and analysis

- FastAPI, Flask, or Django for API development

### AI/ML Expertise

- *RAG Systems*: Hands-on experience building and optimizing RAG pipelines, including:

- Vector databases (Pinecone, Chroma, Weaviate, or similar)

- Embedding models and techniques

- Retrieval strategies and ranking algorithms

- Context window optimization and chunking strategies

- *Large Language Models*: Experience with:

- OpenAI GPT models, Anthropic Claude, or open-source alternatives

- Model fine-tuning and prompt engineering

- Model evaluation and benchmarking

- Cost optimization strategies for LLM usage

### Infrastructure & Deployment

- *Cloud Platforms*: Experience with AWS, GCP, or Azure for AI workload deployment

- *Containerization*: Proficiency with Docker and orchestration tools like Kubernetes

- *Databases*: Experience with both SQL and NoSQL databases, particularly vector databases

- *DevOps*: Familiarity with CI/CD pipelines, infrastructure as code, and monitoring tools

## Preferred Qualifications

### Experience & Background

- Advanced degree in Computer Science, Machine Learning, or related field

- 7+ years of software engineering experience with 3+ years focused on AI/ML

- Experience with real-time AI systems and low-latency inference requirements

- Knowledge of distributed computing and parallel processing frameworks

### Specialized Knowledge

- Experience with multi-agent systems and AI orchestration frameworks

- Familiarity with graph databases and knowledge graph construction

- Understanding of NLP techniques beyond LLMs (NER, sentiment analysis, etc.)

- Experience with computer vision and multi-modal AI applications

- Knowledge of AI safety, alignment, and responsible AI practices

### Leadership & Collaboration

- Experience mentoring junior engineers and leading technical teams

- Strong communication skills for collaborating with cross-functional teams

- Experience working in agile development environments

- Track record of delivering complex AI projects from concept to production

## What We Offer

- Competitive salary and equity compensation

- Comprehensive health, dental, and vision insurance

- Professional development budget for conferences and training

- Flexible work arrangements and remote work options

- Access to cutting-edge AI research and development resources

- Collaborative environment with leading AI researchers and engineers

## Application Process

Please submit your resume along with:

- Portfolio or GitHub repository showcasing relevant AI projects

- Brief cover letter highlighting your RAG and AI deployment experience

- Any relevant publications, blog posts, or technical presentations

We are an equal opportunity employer committed to diversity and inclusion in our workforce.