Senior Gen AI Engineer – Freelancer

• Design, develop, and implement scalable AI and Generative AI solutions aligned with business and product requirements
• Build and productionize LLM-powered applications, intelligent automation systems, and AI-driven workflows
• Partner directly with customers, product teams, and internal stakeholders as a Forward Deployment Engineer
• Translate ambiguous business problems into practical AI architectures, prototypes, and production implementations
• Develop, test, deploy, and optimize AI models and applications across cloud and enterprise environments
• Integrate foundation models and LLM APIs into scalable applications while considering performance, reliability, security, and cost
• Evaluate emerging Generative AI technologies, frameworks, and models for business use cases
• Troubleshoot model and application issues and improve system quality, latency, scalability, and accuracy
• Collaborate with software engineers, data scientists, product managers, and other stakeholders to deliver end-to-end AI solutions
• Develop reusable components, APIs, tools, and frameworks that accelerate AI application deployment
• Establish evaluation, monitoring, and testing approaches for AI and LLM-based systems
• Stay current with Generative AI, LLMs, AI agents, model orchestration, and enterprise AI deployment

• 5–13 years of experience in software engineering, Artificial Intelligence, Machine Learning, or related technical domains
• Strong hands-on experience in AI and Generative AI application development
• Solid understanding of Large Language Models (LLMs), foundation models, prompt engineering, model APIs, and AI application architecture
• Proven experience taking AI solutions from prototype to production
• Strong Forward Deployment Engineering mindset with ability to work directly with users or customers
• Strong programming and software engineering fundamentals
• Experience designing scalable, reliable, and maintainable AI-powered systems
• Ability to independently investigate technical problems and deliver solutions in ambiguous and rapidly changing environments
• Strong communication and collaboration skills across technical and non-technical teams
• Experience with LangChain or similar LLM orchestration frameworks
• Hands-on experience building Agentic AI systems, autonomous workflows, or AI agents
• Experience implementing Retrieval-Augmented Generation (RAG) pipelines
• Knowledge of vector databases, embeddings, semantic search, and document processing
• Familiarity with AI evaluation frameworks, observability, guardrails, and LLM application monitoring
• Experience with cloud platforms and modern deployment practices such as Docker, Kubernetes, and CI/CD
• Exposure to multi-agent architectures, tool calling, function calling, and workflow orchestration