Staff Software Engineer, Applied AI
About The Position
GridUnity is seeking a Staff Software Engineer to join its Platform team, reporting to the Director of Engineering, Applied AI. The engineer will turn the company’s customer workflow vision into reliable capabilities and serve as a technical leader working with Product, Design, engineering, and domain experts. The role owns the technical approach for selected high-value workflows, collaborates on prioritization and engineering acceptance, and coordinates implementation across platform and application teams. The position involves translating customer needs into executable workflows; building and shipping AI-assisted experiences, typed tools, integrations, and orchestration; connecting assistance to completed work; and extending reusable product foundations. The engineer will guide technical execution, evaluate real-world quality, measure customer outcomes, preserve customer trust, and engineer for production reliability and safety. GridUnity builds cloud-based software using TypeScript, React, Node.js, PostgreSQL, AWS, and modern AI tools. The first 90 days are focused on learning the product and customer needs, identifying an AI opportunity in a customer workflow, building and testing an initial solution, gathering feedback, recommending next steps, and helping establish reusable approaches. Success is measured by helping customers complete important work more easily and reliably, not by building demos or increasing AI usage.
Requirements
- 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.
- Ability to partner effectively 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, rather than 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.
- Ability to work directly with customers and domain experts, clarify ambiguous needs, and translate them into bounded, testable solutions.
- Clear communication and ability to raise the effectiveness of other engineers through technical leadership.
Nice To Haves
- Experience with electric utility, interconnection, transmission, distribution, DER, storage, or large-load workflows.
- Experience with regulated or evidence-intensive enterprise applications.
- Experience with TypeScript, Node.js, React, and cloud-based service architectures.
- Experience with document processing, workflow engines, engineering-tool integration, or enterprise authorization models.
- Deep electrical engineering expertise is valuable but not required.
Responsibilities
- Translate customer needs into executable workflows by mapping triggers, outcomes, participants, evidence, decisions, exceptions, and handoffs across workflows and tasks.
- Implement AI-assisted experiences, typed tools, service integrations, and workflow orchestration within the existing application.
- Connect AI assistance to completed work rather than disconnected chat answers, reports, or recommendations.
- Extend reusable product foundations, including runtime, tools, personas, skills, and application services, to improve orchestration, resumability, grounded retrieval, and human approvals.
- Lead technical execution by decomposing opportunities into deliverable increments, resolving cross-team dependencies, and guiding implementation.
- Create representative scenarios and evaluations covering correctness, incomplete information, exceptions, permissions, and failure recovery.
- Partner with Product to establish baselines and assess improvements in effort, correction cycles, throughput, and decision quality.
- Make uncertainty, evidence coverage, source versions, permitted actions, and approval boundaries explicit to preserve customer trust.
- Engineer for production by addressing latency, model and tool costs, observability, safe rollout, failure recovery, prompt injection, and unauthorized tool actions.
- Work directly with customers and domain experts to clarify ambiguous needs and translate them into bounded, testable solutions.
- In the first 90 days, learn the product and customer needs, identify a practical AI workflow opportunity, build and test an initial solution, gather feedback, recommend next steps, and help establish reusable approaches.
Benefits
- Competitive compensation packages recognizing expertise and contributions.
- Remote-first culture providing flexibility and balance.
- Professional development opportunities, including training, mentorship, and career pathing.
- Comprehensive health, dental, and vision insurance starting day one.
- Short- and long-term disability and basic life insurance at no cost.
- 401(k) plan with a 4% match.
- Flexible PTO and a supportive work culture that values balance.
- Mission-driven work with the opportunity to make a significant impact in the energy sector.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
