AI Engineer

What Is the role?

We are seeking a talented AI/GenAI Engineer to design, develop, and deploy AI-driven applications leveraging the power of generative AI models on cloud platforms such as AWS and Azure. The ideal candidate will have a strong background in machine learning, cloud architecture, and software development, with expertise in creating scalable and innovative AI-based solutions tailored to business needs.

Key Responsibilities

Architect and implement advanced AI solutions using state-of-the-art foundation models, focusing on multimodal applications that combine text, vision, and code generation capabilities.
Design and deploy robust AI systems leveraging modern frameworks like LangChain, LlamaIndex, and embedding technologies for RAG (Retrieval Augmented Generation) applications.
Develop and maintain production-grade AI applications using cloud-native architectures, with emphasis on cost optimization and responsible AI practices.
Create and optimize AI agents capable of complex reasoning, tool usage, and autonomous decision-making while ensuring safety and reliability.
Implement efficient vector database solutions (Pinecone, Qdrant, ChromaDB) for semantic search and similarity matching applications.
Build and maintain AI observability systems to monitor model performance, drift, and business impact metrics.
Design hybrid AI architectures combining open-source and proprietary models to optimize for cost, performance, and reliability.
Lead initiatives in developing enterprise-grade AI guardrails and safety mechanisms.

Required Skills

2+ years of experience building AI-driven applications on cloud platforms.
Expertise in modern AI frameworks including LangChain, LlamaIndex, CrewAI, and vector databases.
Strong proficiency in implementing RAG architectures and semantic search solutions using embedding models.
Experience with latest foundation models (Claude 3.5, GPT-4o, Gemini, Llama 3) and their enterprise deployment patterns.
Advanced knowledge of prompt engineering, few-shot learning, and chain-of-thought techniques.
Expertise in AI observability tools (Langfuse, LangSmith, MLflow, Arize) for production monitoring.
Proficiency in modern vector databases and similarity search implementations.
Strong understanding of AI safety, hallucination mitigation, and responsible AI practices.
Experience with containerization and orchestration tools (Docker, Kubernetes) for AI workloads.
Proficiency in deploying AI solutions on AWS (Bedrock, SageMaker, Lambda, ECS, DynamoDB) or Azure (AI Foundry, AI Studio, Document Intelligence, AI Search, OpenAI).
Hands-on experience with fine-tuning generative AI models.

Preferred Skills

Knowledge of latest developments in multimodal AI and their practical applications.
Experience with AI agent frameworks (CrewAI, AutoGen, LangGraph, LlamaIndex Workflows).
Familiarity with quantization techniques and efficient model deployment strategies.
Understanding of latest developments in AI safety and alignment research.
Experience with fine-tuning and prompt engineering for domain-specific applications.
Knowledge of AI-specific security considerations and privacy-preserving techniques.
Expertise in cost optimization strategies for large language model deployments.
Understanding of hybrid search architectures combining traditional and neural approaches.
Proficiency in streaming architectures for real-time AI applications.

Personal Qualities

Strong problem-solving and analytical skills
Excellent communication and teamwork abilities
Self-motivated and able to work independently when required
Passionate about learning new technologies and keeping up with industry trends
Detail-oriented with a focus on writing clean, efficient, and maintainable code

We offer you

Competitive Compensation
Professional Growth
Cutting-Edge Technologies
Highly motivated & collaborative Team
Challenging Projects
Work-Life Balance
Opportunities for Advancement
Employee Well-being