Jop Summary:
You’ll be one of the first engineers on Neumo’s AI team, building the infrastructure and agentic systems that power AI adoption across the entire organization. The work spans three areas:
AI Infrastructure. You’ll build and maintain the engines that make AI work at Neumo: our implementations engine, AI-augmented SDLC tooling, agentic workflow orchestration (n8n, LangGraph, OpenClaw), and integration with our Platform services (MCP, LLM Service, RAG). You’re building the shared foundation that every team at Neumo will eventually consume.
Rapid Skill Creation. You’ll drop into business processes, quickly understand the workflow, and build effective AI-powered skills and automations. Then you’ll hand those skills off to non-technical people so they can maintain and extend them without engineering involvement. The goal is to multiply what everyone at the company can do, not to become a permanent bottleneck.
Staying Current. AI moves fast. You’ll be expected to continuously test new tools, models, frameworks, and patterns, then bring what works back to the team. You’re the person who knows what’s possible today and what’s about to be possible next quarter.
Duties and Responsibilities:
- Design and implement safety, isolation, and governance controls for agents running in production
- Build orchestration pipelines using n8n,LangGraph, or similar frameworks
- Create reusable automation patterns that other teams can adopt without your direct involvement
- Rapidly prototype AI solutions for business processes (support triage, document processing, configuration automation, SDLC workflows)
- Write effective prompts and prompt chains for complex multi-step tasks
- Optimizefor cost, latency, and accuracy across LLM providers
- Contribute to the AI-augmented SDLC: coding assistants, automated testing, deployment automation, ticket quality validation
- Hand off completed skills and automations to non-technical operators with clear documentation
- Perform other duties as assigned
Education and Experience:
- 3+ years of software engineering experience, building and shipping production systems
- A degree in AI, ML, or data science. We care about what you’ve built.
- Hands-on experience building applications that integrate with LLMs (prompt engineering, API integration, structured output parsing)
- Experience with agentic patterns: tool use, multi-step reasoning, human-in-the-loop workflows
- Experience with cloud platforms (AWS preferred)
- Experience with agentic orchestration frameworks (Lang Graph, n8n,CrewAI, or similar)
- Experience with RAG architectures (vector databases, document chunking, retrieval optimization)
- Experience with Claude, Cursor, or similar AI-assisted development tools
- Experience building systems that non-technical users operate and maintain
- Experience mapping end-to-end business processes and identifying which steps can be automated vs. which require human judgment
Knowledge, Skills and Abilities:
- Strong fundamentals in at least one backend language (Node.js preferred, Python also valued)
- Comfort working across the stack when needed (APIs, databases, cloud infrastructure, basic frontend)
- Strong communication skills, both written and verbal. You’ll work with non-technical stakeholders regularly.
- Ability to learn new tools and frameworks quickly. The landscape changes monthly.
- Familiarity with MCP (Model Context Protocol) or similar LLM connectivity patterns
- Understanding of LLM cost optimization (model selection, caching, prompt efficiency)
- ML/model training experience. We use LLMs as services, not train them.
- Government or gov-tech experience. Helpful context, but not a filter.
How We Work:
- Agentic-first, not chatbot-first.We build agents with human-in-the-loop verification, not chat interfaces.
- Centralized agent development.All new agent work runs through this team until risk and patterns are well understood.Youown build, ops, and governance.
- Shared services model.You build on Platform’s foundation (MCP, LLM Service, RAG) and create reusable patterns. No one-off implementations thatdon’tgeneralize.
- Speed matters.We’rein a 1-year competitive window. Bias for action, rapid prototyping, and fast iteration.
- Tools:Claude, TypeScript, Node.js, AWS, n8n, Jira, Confluence.
What Success Looks Like (First 6-12 Months):
- Multiple agentic workflows running in production, handling real work
- Reusable automation patterns documented and adopted by at least one product team
- Non-technical operators running and maintaining skills you built
- Measurable reduction in manual effort for at least two business processes
- Active contribution to the team’s understanding of emerging AI tools and patterns
Work Environment:
- Office setting with a moderate noise level.
- The employee will work at an individual workstation, using a telephone and computer.
Physical Demands:
- Must be able to remain seated for extended periods.
- Regular use of a computer and other office machinery, such as printers and copy machines.
- Occasional movement around the office.
- Frequent communication via telephone.
Neumo Summary:
With the backing of four decades of public sector expertise and corporate capability, Neumo has successfully supported government services. Neumo was honored and recognized for four (4) consecutive years as a GovTech 100 Company representing the top 100 companies focused on making a difference in and selling to state and local government agencies across the United States.
Neumo is committed to helping communities thrive and brings a wealth of experience combined with innovation. Today, Neumo offers more administrative and financial support to government officials than any other organization. And with a responsive, client-focused approach, we foster partnerships that give our customers the certainty they need to accomplish more.
Neumo offers a competitive benefits and compensation package and are looking for team members who will thrive in our dynamic environment.
Neumo is an Equal Opportunity Employer. Selection for a position will be made without regard to race, religion, national origin, sex, political affiliation, marital status, non-disqualifying physical handicap, and age.