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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - **Company:** UMAN LLC - **Location:** Chicago, IL, United States - **Experience:** Experienced - **Salary:** $130,000.0 - $170,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Software Applications, Computer Vision, Microsoft Azure, Cloud Computing, Continuous Integration, Data Security, Software Debugging, DevOps, Python (Programming Language), Machine Learning, OpenAI, Software Engineering, TypeScript, Large Language Models, Prompt Engineering, Model Validation, Generative AI, Backend, AI Platforms, Front End Software Development, Google Gemini, Data Pipelines, Docker - **Published:** October 6, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=37e4c895ac8346b9 ## About the Role * Approximately 8 years engineering experience that includes at least 4 years building AI-powered systems, or equivalent hands-on experience shipping AI in production systems. * Hands-on experience with LLMs, embeddings, vector databases, prompt and context engineering, retrieval setups, fine-tuning, and model evaluation. * Experience building agents, including memory, tool use, and orchestration, with at least one modern agent framework. * Experience integrating AI services such as OpenAI, Azure OpenAI, Anthropic, Google Gemini, and Meta models. * Strong software engineering skills in TypeScript and/or Python, including real backend systems and data pipelines. * Full-stack product thinking: frontend or backend experience outside the traditional AI field, and the ability to build end to end. * Proven experience deploying and running scalable applications in Azure, GCP, or AWS. * Experience with Docker, CI/CD, and modern DevOps practices. You can take a solution from "it works on my laptop" to "it runs reliably in the cloud." * A track record of delivering AI solutions, not just prototypes. * A pragmatic mindset and the judgment to know when AI is the right tool and when it isn't. * The ability to turn vague questions into concrete technical solutions for our clients. * Strong communication skills and comfort working in multidisciplinary teams. * Curiosity about emerging AI capabilities, creativity in applying them, and enthusiasm for exploring new approaches. Nice-to-haves * Experience with machine learning, computer vision, generative images, and/or multimodal models. * Experience in consultancy or client-facing environments. ## Description As an AI Engineer at Umain, you'll build the next generation of AI-powered products, workflows, and agents for our clients, combining strong software engineering fundamentals and full-stack product thinking with modern AI capabilities. Your work will range from integrating LLMs and vision models to architecting agents, building scalable pipelines and experimenting with new techniques. You'll turn ambiguous ideas into robust solutions, evaluate where AI truly adds value and help clients understand what is possible, feasible, and responsible-all while playing an active role in shaping our growing AI practice. What you'll do * Partner with clients to clarify their challenges, decide whether AI is the right answer and assess feasibility and risk, including data security, privacy, licensing, and responsible AI. * Design, prototype, build, and ship AI-powered applications, workflows, and agents for clients ranging from start-ups to global enterprises. * Architect agentic systems, including context management, memory, orchestration, and the tools, skills, and MCP integrations agents rely on. * Select, integrate, and adapt foundation models (OpenAI, Anthropic, Google, and others). Fine-tune or combine them when off-the-shelf options fall short. * Design around model limitations in both the architecture and the product's UX. Apply techniques like retrieval, chunking, embeddings, and redlining, and debug AI systems when they misbehave. * Build evaluation and observability into everything you ship. Use stochastic test cases, trace-based analysis, and tools to benchmark and monitor models, prompts, and agents. * Build the software, data pipelines, and cloud infrastructure (Azure, GCP, or AWS) that keep AI products running reliably at scale. * Own parts of project delivery, communicate clearly with technical and non-technical stakeholders, and lead client and internal workshops. * Bring technical credibility to new business. You'll join pitches as our AI expert, shape proposals and RFP responses, and help prospective clients see what's possible. * Help define Umain's AI offerings and grow the competence through internal frameworks, playbooks, knowledge sessions, and engineering standards. What you'll do * Partner with clients to clarify their challenges, decide whether AI is the right answer and assess feasibility and risk, including data security, privacy, licensing, and responsible AI. * Design, prototype, build, and ship AI-powered applications, workflows, and agents for clients ranging from start-ups to global enterprises. * Architect agentic systems, including context management, memory, orchestration, and the tools, skills, and MCP integrations agents rely on. * Select, integrate, and adapt foundation models (OpenAI, Anthropic, Google, and others). Fine-tune or combine them when off-the-shelf options fall short. * Design around model limitations in both the architecture and the product's UX. Apply techniques like retrieval, chunking, embeddings, and redlining, and debug AI systems when they misbehave. * Build evaluation and observability into everything you ship. Use stochastic test cases, trace-based analysis, and tools to benchmark and monitor models, prompts, and agents. * Build the software, data pipelines, and cloud infrastructure (Azure, GCP, or AWS) that keep AI products running reliably at scale. * Own parts of project delivery, communicate clearly with technical and non-technical stakeholders, and lead client and internal workshops. * Bring technical credibility to new business. You'll join pitches as our AI expert, shape proposals and RFP responses, and help prospective clients see what's possible. * Help define Umain's AI offerings and grow the competence through internal frameworks, playbooks, knowledge sessions, and engineering standards.