Senior Gen AI Engineer – Freelancer
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Job Description
Senior Gen AI Engineer building production AI and LLM applications for a technology, media, and information client. Delivering customer-focused solutions from prototypes through deployment and optimization.
Responsibilities:
- 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, considering performance, reliability, security, and cost
- Evaluate emerging Gen 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
Requirements:
- 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 the ability to work directly with users or customers and rapidly build solutions around their requirements
- 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, particularly when working 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
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