Senior Engineer - Artificial Intelligence

JOB OVERVIEW

We are seeking a highly skilled and experienced Senior AI Engineer to lead the design, development, and deployment of advanced AI-powered solutions across our products and internal platforms. This role requires a strong combination of software engineering expertise, AI/ML knowledge, strategic thinking, and leadership capabilities.

As a Lead AI Engineer, you will not only architect and deliver cutting-edge AI solutions but also lead a team of AI engineers, driving technical excellence, innovation, and successful project delivery. You will play a critical role in defining our AI roadmap, mentoring engineers, establishing development standards, and ensuring the successful execution of AI initiatives across the business.

This is a hands-on leadership role where you will balance technical contributions with team management responsibilities while helping shape the future of AI within the organization.

Key Responsibilities

AI Architecture & Development

• Design, develop, and deploy production-grade AI solutions using modern AI frameworks, LLMs, and machine learning technologies.
• Architect scalable AI systems, including RAG (Retrieval-Augmented Generation), AI agents, multi-agent workflows, knowledge bases, and intelligent automation platforms.
• Evaluate and integrate emerging AI technologies, models, and tools into existing products and engineering workflows.
• Build AI-powered applications leveraging OpenAI, Anthropic, Google Gemini, Azure AI, and open-source models.
• Develop AI solutions that improve business processes, customer experience, operational efficiency, and decision-making.

Engineering Leadership

• Lead technical design discussions and establish best practices for AI development and deployment.
• Mentor and guide junior AI engineers and developers.
• Conduct architecture reviews, code reviews, and technical assessments.
• Drive AI governance, security, scalability, and responsible AI practices across projects.

Product & Platform Development

• Collaborate with product managers, designers, and engineering teams to deliver AI-enabled product features.
• Design and develop full-stack AI applications using React.js, Next.js, Node.js, and cloud-native technologies.
• Build and maintain APIs, microservices, and AI orchestration layers.
• Integrate third-party AI services, enterprise platforms, and external APIs.

ML Ops & Infrastructure

• Implement CI/CD pipelines for AI applications and machine learning deployments.
• Monitor, optimize, and maintain AI systems in production environments.
• Manage vector databases, embeddings, model evaluation frameworks, and AI observability tools.
• Optimize performance, scalability, reliability, and cost efficiency of AI solutions.

Research & Innovation

• Stay current with advancements in generative AI, machine learning, AI agents, and emerging technologies.
• Conduct proof-of-concepts and technical evaluations for new AI initiatives.
• Identify opportunities to leverage AI to improve engineering productivity and business operations.

Required Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field.
• 4-6 years of software engineering experience with at least 3+ years focused on AI/ML or Generative AI solutions.
• Strong hands-on experience with Python and modern AI development frameworks.
• Experience building and deploying applications using Large Language Models (LLMs).
• Proficiency with frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Semantic Kernel, or similar.
• Experience implementing RAG pipelines, vector databases, embeddings, and knowledge retrieval systems.
• Strong understanding of prompt engineering, model evaluation, fine-tuning concepts, and AI application architecture.
• Experience working with OpenAI, Azure OpenAI, Anthropic Claude, Gemini, or open-source LLMs.
• Strong experience with REST APIs, microservices, and distributed systems.
• Experience with cloud platforms such as Azure, AWS, or Google Cloud.
• Strong knowledge of SQL, NoSQL databases, and data architecture.
• Experience with Git, CI/CD pipelines, Docker, Kubernetes, and DevOps practices.
• Excellent problem-solving, analytical, and communication skills.

Preferred qualifications

• Experience building and deploying AI agents and autonomous workflow systems.
• Experience with machine learning model development and ML Ops practices.
• Experience working with vector databases such as Pinecone, Weaviate, Chroma, Qdrant, or Azure AI Search.
• Knowledge of AI governance, security, privacy, and responsible AI frameworks.
• Experience in education technology, travel technology, SaaS, or enterprise software products.
• Experience leading technical teams or mentoring engineers.
• Contributions to open-source AI projects, research publications, or AI communities.