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# Staff Software Engineer

- **Company:** Grid Unity, Inc.
- **Location:** United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Application Services, Software as a Service, Cloud Computing, PostgreSQL, Node.Js, Software Engineering, TypeScript, Enterprise Software Applications, ReactJS, Virtual Agents
- **Published:** November 7, 2026
- **Apply:** https://startup.jobs/staff-software-engineer-applied-ai-gridunity-10705273

## About the Role

* Demonstrable experience delivering customer-facing software and leading consequential technical work across teams or services.
 * Hands-on experience building production AI applications that retrieve information, invoke tools, or coordinate multi-step work.
 * Effective at partnering with qualified experts rather than substituting AI judgment for engineering authority.
 * Strong software engineering skills, including APIs, structured contracts, asynchronous execution, testing, and observability.
 * Experience connecting AI capabilities to real application state and authorized actions-not only building conversational prototypes.
 * Sound judgment about where deterministic logic, AI assistance, and human decisions belong.
 * Experience designing evaluations and investigating failures involving incomplete data, ambiguous requirements, or unreliable model outputs.
 * The ability to work directly with customers and domain experts, clarify ambiguous needs, and translate them into bounded, testable solutions.
 * Clear communication and the ability to raise the effectiveness of other engineers through technical leadership.

Preferred experience

 * Electric utility, interconnection, transmission, distribution, DER, storage, or large-load workflows.
 * Regulated or evidence-intensive enterprise applications.
 * TypeScript, Node.js, React, and cloud-based service architectures.
 * Document processing, workflow engines, engineering-tool integration, or enterprise authorization models.
 * Deep electrical engineering expertise is valuable but not required.

Our technology

We build cloud-based software using TypeScript, React, Node.js, PostgreSQL, and AWS, alongside modern AI tools.

You do not need experience with every tool we use. We value sound engineering judgment and a track record of delivering reliable software that solves real customer problems.

## Description

GridUnity is seeking a Staff Software Engineer to join our Platform team, reporting to the Director of Engineering, Applied AI. You will turn our customer workflow vision into reliable capabilities .

You will be the dedicated technical leader partnering closely with Product, Design, engineering, and domain experts to discover high-value opportunities, build workflow capabilities, and help ensure we deliver measurable customer outcomes. You will own the technical approach for selected high-value workflows, collaborating with Product on prioritization, domain experts on engineering acceptance, and platform and application teams on implementation., * Translate customer needs into executable workflows. Map triggers, desired outcomes, participants, evidence, decisions, exceptions, and handoffs across full workflows and their constituent tasks.

 * Build and ship capabilities. Implement AI-assisted experiences, typed tools, service integrations, and workflow orchestration within the existing application.
 * Connect the experience end-to-end. Ensure assistance leads to completed work-not disconnected chat answers, reports, or recommendations.
 * Extend reusable foundations. Build on our product's existing runtime, tools, personas, skills, and application services to improve reliable orchestration, resumability, grounded retrieval, and human approvals.
 * Lead technical execution. Decompose opportunities into deliverable increments, resolve cross-team dependencies, and guide implementation without becoming the sole implementer.
 * Evaluate real-world quality. Create representative scenarios and evaluations covering correctness, incomplete information, exceptions, permissions, and failure recovery.
 * Measure customer outcomes. Partner with Product to establish baselines and assess improvements in effort, correction cycles, throughput, and decision quality.
 * Preserve customer trust. Make uncertainty, evidence coverage, source versions, permitted actions, and approval boundaries explicit.
 * Engineer for production. Address latency, model and tool costs, observability, safe rollout, failure recovery, prompt injection, and unauthorized tool actions., * Identify a practical opportunity for AI to improve a customer workflow.
 * Build and test an initial solution, gather feedback, and recommend next steps.
 * Help establish approaches the team can reuse.