Lead Machine Learning Engineering

Role Overview

We are looking for a Senior AI Engineer who can design, build, and deploy production-ready AI solutions using modern Large Language Models (LLMs), AI agents, and cloud-native architectures. The ideal candidate combines strong software engineering fundamentals with hands-on experience building scalable AI applications, integrating foundation models, and delivering business value through Generative AI.

Key Responsibilities

• Design, develop, and maintain AI-powered applications using Large Language Models

(LLMs) and Generative AI technologies

• Build AI agents and Retrieval-Augmented Generation (RAG) solutions to enable intelligent workflows and knowledge-based applications.

• Integrate leading AI platforms such as Azure OpenAI, Amazon Bedrock, Google Vertex AI, or similar services.

• Develop scalable backend services and APIs using Python and modern frameworks such as FastAPI.

• Collaborate with frontend engineers to deliver end-to-end AI applications using technologies such as React.

• Design prompt engineering strategies to improve model accuracy, reliability, and user experience.

• Implement intelligent routing, semantic search, vector databases, and knowledge retrieval solutions.

• Deploy and manage cloud-native AI applications using AWS and Infrastructure as Code tools such as Terraform.

• Build and maintain CI/CD pipelines, containerized applications, and cloud infrastructure using Docker and DevOps best practices.

• Evaluate emerging AI frameworks, tools, and models to continuously improve platform capabilities.

• Collaborate with Product Managers, Architects, and Engineering teams to translate business requirements into scalable AI solutions.

• Mentor engineers and contribute to technical leadership, architecture discussions, and engineering best practices.

Required Qualifications

• 10+ years of experience in Software Engineering with recent hands-on experience building Generative AI solutions.

• Strong experience with Python and REST API development.

• Experience developing production AI applications using Large Language Models (LLMs).

• Hands-on experience with AI agent frameworks such as LangChain, CrewAI, or similar technologies.

• Experience implementing Retrieval-Augmented Generation (RAG) architectures.

• Experience integrating AI platforms such as Azure OpenAI, Amazon Bedrock, Google Vertex AI, or equivalent services.

• Strong understanding of prompt engineering techniques and AI application design patterns.

• Experience developing scalable cloud applications on AWS.

• Experience with Docker, Terraform, CI/CD pipelines, and Infrastructure as Code.

• Experience with SQL and NoSQL databases.

• Familiarity with React or modern frontend technologies.

• Experience working within Agile software development environments.

• Strong understanding of software architecture, API design, and distributed systems.

• Experience working in cross-functional and multicultural teams.

Working Style

• Strong communication skills: able to clearly explain complex AI concepts to both technical and non-technical audiences.

• Proactive mindset: identifies opportunities for innovation and continuously explores new AI technologies.

• Ownership and accountability: takes responsibility for delivering reliable, scalable, and maintainable AI solutions.

• Collaborative attitude: works effectively across product, engineering, architecture, and business teams.

• Adaptability: thrives in a rapidly evolving AI landscape and embraces continuous learning.

• Attention to detail: prioritizes quality, security, observability, and responsible AI practices.

• Customer-oriented thinking: focuses on solving real business problems through practical AI solutions.

• Continuous learner: stays current with advancements in LLMs, AI frameworks, cloud services, and software engineering best practices