Description

What's the Job?

• Embed with internal teams and external customers to understand real workflows, pain points, and goals—then design and deploy solutions that fit operational needs.
• Build and deploy production-quality agentic AI systems (voice agents, chat agents, copilots, automation workflows) alongside data integrations and custom software to solve concrete business problems.
• Design and implement RAG pipelines, prompt orchestration layers, and multi-agent workflows tailored to real enterprise environments and BU-specific data.
• Integrate data pipelines, APIs, and third-party systems while handling the real-world messiness of enterprise deployments.
• Own outcomes after launch by monitoring and improving reliability, performance, and adoption—success is measured by business impact, not activity metrics.

What's Needed?

• 8+ years building and shipping software in production, including end-to-end ownership of complex, ambiguous projects with minimal supervision.
• Python required as the primary language, plus strong proficiency in at least one additional language (JavaScript/TypeScript, Java, or Go).
• Hands-on AI/GenAI engineering experience deploying LLM-based systems in production, including prompt engineering, RAG architecture, and agent orchestration (LangChain, LlamaIndex, or equivalent).
• Data platform fluency: complex SQL and ETL/ELT pipelines; experience with data warehouses such as Snowflake, Databricks, or equivalent.
• Cloud & DevOps capability: comfort deploying to AWS, GCP, or Azure; working with Docker and CI/CD pipelines

Key Skills

Education

Any Graduate