AI Engineer - Enterprise Agent Development

Role Overview: Join the Team Revolutionizing Procurement Analytics at SenseCloud. Sensecloud envisions a future where Procurement data management and analytics is as intuitive as your favorite app. They are redefining procurement analytics to provide real-time insights, automation, and a frictionless experience for quick decision-making. As an AI Engineer, you will be designing, implementing, and productionizing LLM-powered agents to solve real-world enterprise problems. You will work on multi-agent systems, fine-tune LLMs, integrate agents with enterprise data sources, and own the MLOps lifecycle. Key Responsibilities: - Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. - Fine-tune and prompt-engineer LLMs for retrieval-augmented generation (RAG), reasoning, and tool use. - Integrate agents with enterprise data sources and downstream applications. - Own the MLOps lifecycle including containerization, CI/CD automation, monitoring, and more. - Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and features. - Benchmark & iterate on latency, cost, and accuracy, design experiments, run A/B tests, and present findings to stakeholders. - Stay current with GenAI landscape and champion best practices in ethical AI, data privacy, and security. Qualifications Required: - 3-5 years of software engineering or ML experience in production environments. - Strong Python skills, familiarity with TypeScript/Node or Go is a bonus. - Hands-on experience with LLM/agent frameworks and platforms. - Solid grasp of vector databases and embedding models. - Experience building and securing REST/GraphQL APIs and microservices. - Cloud skills on AWS, Azure, or GCP. - Proficiency with Git, Docker, CI/CD, and ML Ops tooling. - Soft skills: product mindset, communication, collaboration & ownership, bias for action, growth attitude. - Nice-to-have: experience with RAG pipelines, MCP servers/clients, LLM evaluation frameworks, Palantir/Foundry, privacy-enhancing techniques, conversational UX, open-source AI projects. (Note: Omitted the additional details of the company as it was not provided in the JD),