Sr AI Engineer

Job Title: Senior AI Engineer – Generative AI & AI Product Development

Experience: 7+ years in software engineering / development, including 2+ years of hands-on AI engineering experience Role Type: Hands-on Engineering, AI Solution Architecture & Consulting

Position Overview

We are seeking a highly skilled, hands-on Senior AI Engineer with a strong background in software development or engineering who has successfully transitioned into building and delivering production-grade AI solutions.

The ideal candidate is currently working as an AI Engineer and has demonstrated experience designing, developing, deploying, and scaling AI-powered products from concept through production.

This individual must have practical experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Claude, OpenAI Codex, AI agents, and modern Generative AI development frameworks.

Beyond technical expertise, the candidate should bring strong consulting capabilities, having worked directly with both internal business stakeholders and external clients to understand business challenges, recommend AI solutions, and lead their successful implementation.

We are looking for an engineer who can architect solutions, write production-quality code, build AI products, and communicate effectively with technical and business stakeholders—not someone whose experience is limited to AI research, experimentation, or proof-of-concept development.

Key Responsibilities

• End-to-End AI Product Engineering
• Own the complete AI product development lifecycle, including requirements gathering, solution design, architecture, hands-on development, testing, deployment, and production support.
• Design and build scalable, reliable, secure AI applications that solve real business problems.
• Translate business requirements into technical designs and production-ready AI solutions.
• Develop AI-powered applications, intelligent assistants, agentic workflows, and enterprise AI platforms.
• Integrate AI capabilities into existing enterprise applications, APIs, and business workflows.
• Establish production monitoring, performance optimization, evaluation, and continuous improvement processes.
• Generative AI, LLMs & RAG Development
• Demonstrate hands-on experience building applications using Claude (Anthropic), OpenAI models, and other leading LLM platforms.
• Leverage Claude Code and OpenAI Codex for AI-assisted software engineering, code generation, refactoring, testing, and development workflows.
• Design and implement Retrieval-Augmented Generation (RAG) architectures for enterprise knowledge retrieval, document intelligence, and contextual AI applications.
• Work with embeddings, vector databases, semantic search, document ingestion, chunking strategies, and retrieval optimization.
• Develop and orchestrate AI agents and multi-step workflows using appropriate frameworks and tools.
• Implement prompt engineering, context management, tool/function calling, structured outputs, and LLM evaluation techniques.
• Optimize AI applications for accuracy, latency, reliability, security, and cost.
• Software Engineering & Solution Architecture
• Apply strong software engineering principles to AI product development, including clean architecture, modular design, reusable components, and automated testing.
• Develop backend services, APIs, and integrations using Python and/or other modern programming languages.
• Design scalable architectures using cloud platforms such as AWS, Azure, or Google Cloud.
• Implement CI/CD pipelines, containerization, deployment automation, and production observability.
• Work with databases, distributed systems, microservices, and enterprise integration patterns.
• Ensure AI applications meet enterprise standards for security, data privacy, scalability, and maintainability.
• Internal & External Consulting
• Serve as a trusted technical advisor to internal business teams, technology leadership, and external clients.
• Conduct discovery sessions and technical workshops to identify business opportunities where AI can deliver measurable value.
• Evaluate business requirements and recommend appropriate AI architectures, technologies, and implementation strategies.
• Present AI solution designs, technical recommendations, and implementation roadmaps to technical and nontechnical audiences.
• Partner with clients and internal stakeholders throughout the project lifecycle, from initial consultation through production delivery.
• Provide technical guidance on AI feasibility, adoption, integration, and operational readiness.
• Balance technical trade-offs, business objectives, delivery timelines, and implementation costs.
• Production Deployment & AI Operations
• Deploy and maintain AI applications in real-world production environments.
• Build evaluation and monitoring frameworks to assess model performance, retrieval quality, hallucination risks, and overall system reliability.
• Implement LLMOps/MLOps practices, automated testing, logging, tracing, and version management.
• Address production challenges involving scalability, response quality, latency, security, and cost.
• Continuously improve deployed AI solutions based on performance metrics, business feedback, and user adoption.

Required Qualifications

Professional Experience

• 7+ years of professional software development or engineering experience, with a strong foundation in application development, backend engineering, full-stack engineering, or solution architecture.
• 2+ years of recent, hands-on experience in AI engineering, specifically building Generative AI and LLM-powered applications.
• Currently working in an AI Engineer, Senior AI Engineer, Generative AI Engineer, or equivalent hands-on AI development role.
• Proven experience delivering at least one AI-powered product or enterprise AI application from initial design through successful production deployment.
• Demonstrated experience supporting production AI solutions beyond proof-of-concept or prototype stages.
• Experience in a consulting, professional services, client-facing engineering, or technical advisory capacity.
• Experience collaborating directly with both internal business stakeholders and external customers or clients.