Senior Value Engineer (public Sector) - Sacramento, Ca

Celonis Celonis · Data AI · Redwood City, CA +1 · Value Engineering

This role focuses on applying AI and Process Intelligence to solve operational challenges for Public Sector clients, specifically State and Local Governments. The Senior Value Engineer will prototype and demonstrate AI solutions, focusing on agentic systems with RAG and tool integration, while ensuring compliance with government security and data frameworks. The role involves both pre-sales and post-sales activities, including hackathons and proof-of-value projects, aiming to industrialize AI within government agencies.

What you'd actually do

  1. Understand public sector AI strategies and specific agency challenges (e.g., benefits administration backlogs, procurement bottlenecks, public safety resource allocation, or permitting delays). As a Celonis product and government domain expert, find the best problem-solution fit and translate agency requirements into innovative solutions that deliver measurable public impact.
  2. Lead technical discovery and capability demonstrations during the complex government pre-sales and procurement (RFP) cycles, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are successfully met.
  3. Leverage cutting-edge AI technologies to rapidly build creative prototypes in agency hackathons, solving critical pain points to improve constituent experiences.
  4. Support our government customers in achieving real value out of AI deployments at scale, enabling a fundamental shift from traditional, rigid, paper-heavy workflows to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., intelligent case triaging or automated compliance checks).
  5. End-to-end execution of critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with government enterprise data, identity protocols, and stringent compliance/security frameworks (e.g., StateRAMP, HIPAA, CJIS).

Skills

Required

  • 5+ years of experience leading technical pre-sales and post-sales engagements specifically within the Public Sector (State & Local Government)
  • Deep understanding of business processes native to state and local governments
  • Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning
  • Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch)
  • Strong presentation skills

Nice to have

  • Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering
  • Experience in deploying and monitoring models at scale within government-compliant cloud environments (e.g., AWS GovCloud, Azure Government)
  • Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages

What the JD emphasized

  • 5+ years of experience leading technical pre-sales and post-sales engagements specifically within the Public Sector (State & Local Government)
  • Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases
  • architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with government enterprise data, identity protocols, and stringent compliance/security frameworks (e.g., StateRAMP, HIPAA, CJIS)
  • Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails suited for highly scrutinized public sector environments.

Other signals

  • building AI solutions for public sector clients
  • prototyping AI solutions
  • demonstrating value to government CIOs
  • ensuring successful implementation and adoption
  • architecting and delivering secure, scalable LLM/agent systems