← Back to Careers

AI Engineer

Apply Now

Remote

Posted on: January 5, 2026

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 LangGraph, LangChain, LlamaIndex, and Google ADK for building stateful, multi-agent workflows.
  • Develop and maintain production-grade AI applications using cloud-native architectures on AWS Bedrock, Azure AI Foundry, and Google Vertex AI, with emphasis on cost optimization and responsible AI practices.
  • Build sophisticated AI agents and multi-agent systems using AWS Bedrock Agents, Azure AI Foundry Agent Service, and frameworks like LangGraph and CrewAI for complex reasoning and autonomous decision-making.
  • Implement comprehensive AI observability and evaluation frameworks using tools like LangSmith, Opik, Langfuse, Arize, and Phoenix for monitoring model performance, quality metrics, and business impact.
  • Design and execute rigorous evaluation strategies including LLM-as-judge, human-in-the-loop evals, and automated testing pipelines to ensure AI system reliability and accuracy.
  • Implement efficient vector database solutions (Pinecone, Qdrant, ChromaDB, Weaviate) for semantic search and similarity matching applications.
  • 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, safety mechanisms, and evaluation frameworks.

Required Skills

  • 2+ years of experience building AI-driven applications on cloud platforms.
  • Expertise in modern AI frameworks including LangGraph, LangChain, LlamaIndex, Google ADK, and CrewAI for building stateful agent workflows.
  • Strong proficiency in implementing RAG architectures and semantic search solutions using embedding models and hybrid search strategies.
  • Advanced knowledge of prompt engineering, few-shot learning, chain-of-thought, and ReAct prompting techniques.
  • Expertise in AI observability and evaluation tools (LangSmith, Opik, Langfuse, Arize, Phoenix, MLflow) for production monitoring and quality assurance.
  • Strong experience designing and implementing evaluation frameworks including LLM-as-judge, automated evals, and human feedback loops.
  • Proficiency in modern vector databases (Pinecone, Qdrant, Weaviate, ChromaDB) and similarity search implementations.
  • Strong understanding of AI safety, hallucination mitigation, guardrails implementation, and responsible AI practices.
  • Experience with containerization and orchestration tools (Docker, Kubernetes) for AI workloads.
  • Proficiency in deploying AI solutions on AWS (Bedrock, Bedrock Agents, SageMaker, Lambda) or Azure (AI Foundry, AI Studio, Agent Service, Document Intelligence, AI Search).
  • Hands-on experience with fine-tuning and evaluation of generative AI models.

Preferred Skills

  • Knowledge of latest developments in multimodal AI and their practical applications including vision-language models.
  • Experience with advanced AI agent frameworks (LangGraph, Google ADK, AutoGen, LlamaIndex Workflows) for building complex multi-agent systems.
  • Hands-on experience with AWS Bedrock Agents, Azure AI Foundry Agent Service, and agent orchestration patterns.
  • Expertise in building comprehensive evaluation pipelines including unit tests for LLMs, regression testing, and A/B testing frameworks.
  • Understanding of latest developments in AI safety, alignment research, and constitutional AI principles.
  • Experience with fine-tuning techniques (LoRA, QLoRA, full fine-tuning) and prompt engineering for domain-specific applications.
  • Knowledge of AI-specific security considerations, privacy-preserving techniques, and PII detection/redaction.
  • Expertise in cost optimization strategies for large language model deployments including caching and model routing.
  • Understanding of hybrid search architectures combining traditional and neural approaches (BM25 + vector search).
  • Proficiency in streaming architectures for real-time AI applications and event-driven agent systems.
  • Experience with synthetic data generation and data augmentation for AI training and evaluation.

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
Apply Now