N

Neuroscale AI

AI-driven document evaluation for federal workflows

Forward Deployed Engineer

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeReston, VA, USA

About the Job

Requirements

  • At least 5 years of experience in software engineering, solution engineering, technical consulting, customer-facing engineering, implementation engineering, or forward deployed engineering.
  • Strong hands-on programming experience with Python, TypeScript, JavaScript, Node.js, or similar modern languages.
  • Experience building or integrating production software systems using REST APIs, webhooks, OAuth, SSO/SAML, databases, cloud services, and enterprise application integrations.
  • Experience working with cloud environments such as AWS, Azure, or GCP.
  • Strong understanding of modern AI/ML and GenAI concepts, including LLMs, RAG, embeddings, vector search, prompt engineering, evaluation, and workflow orchestration.
  • Ability to work directly with enterprise IT and security teams on authentication, access control, logging, data privacy, data residency, and deployment requirements.
  • Willingness to travel for customer workshops, onsite deployments, executive briefings, and go-lives.

Responsibilities

  • Own customer deployments from discovery through go-live, including workflow mapping, solution design, implementation, testing, launch, and post-launch optimization.
  • Work directly with recruiting leaders, HR teams, talent acquisition operations, IT/security teams, and executive stakeholders to understand business goals and translate them into technical solutions.
  • Configure and customize Arbi workflows for resume screening, candidate matching, recruiter copilots, automated outreach, interview workflows, compliance review, talent pipeline analytics, and enterprise reporting.
  • Build and maintain integrations with ATS, HRIS, CRM, LMS, identity providers, email/calendar systems, job boards, and customer data environments.
  • Support production rollouts for enterprise, public sector, and higher-education customers.
  • Design and implement AI-powered workflows using LLMs, RAG, structured evaluation rubrics, candidate scoring logic, document intelligence, and agentic automation.
  • Help customers define evaluation criteria, scoring rubrics, workflow automation rules, and human-in-the-loop review patterns.
  • Work with product and ML teams to improve prompt chains, model evaluation, retrieval quality, explainability, auditability, and customer-specific performance.
  • Support safe, reliable, and explainable AI deployments with clear logging, traceability, monitoring, and customer-facing outputs.
  • Serve as the voice of the customer to the product and engineering teams.
  • Identify repeatable customer patterns and turn them into reusable templates, product features, implementation accelerators, and reference architectures.
  • Write technical documentation, deployment guides, integration notes, customer playbooks, and implementation best practices.
  • Partner with sales, customer success, product, and engineering teams during pilots, demos, enterprise evaluations, renewals, and expansions.
  • Troubleshoot integration issues, API failures, data mapping problems, authentication flows, permissions, system performance, and customer environment constraints.
  • Rapidly prototype solutions when customer requirements are ambiguous or evolving.
  • Make practical engineering tradeoffs to deliver customer outcomes quickly without introducing unnecessary complexity.

Desired Qualifications

  • Experience deploying AI, SaaS, HR Tech, recruiting tech, workflow automation, document intelligence, or enterprise analytics platforms.
  • Experience integrating with systems such as Workday, Greenhouse, Lever, iCIMS, Bullhorn, Salesforce, HubSpot, ServiceNow, Microsoft 365, Google Workspace, or similar enterprise platforms.
  • Experience with databases and search systems such as PostgreSQL, Redis, OpenSearch, Elasticsearch, Pinecone, Weaviate, or other vector databases.
  • Experience with Docker, Kubernetes, CI/CD pipelines, observability tools, and production monitoring.
  • Experience in public sector, federal, higher education, staffing, HR, talent acquisition, or workforce development environments.
  • Prior experience at an early-stage startup or in a high-growth customer-facing technical role.

About the Company

Neuroscale AI

AI-driven document evaluation for federal workflows

Neuroscale AI builds an AI-powered platform that helps federal agencies and similar organizations speed up how they process documents. It automates tasks like screening resumes, evaluating proposals, checking compliance, assessing interviews, and evaluating customer service, all through AI-driven analysis embedded in a cloud-based workflow. This means users upload or feed documents into Neuroscale AI, and the platform analyzes them to produce results, rankings, and insights that teams can act on, reducing manual review time and speeding decision-making. The service is sold on a subscription basis with scalable options tailored to each client’s needs. Neuroscale AI differentiates itself by targeting government and similarly complex organizations, offering end-to-end automation of document processing within customized workflows, rather than generic, one-off tools. Its overall goal is to help clients save time, improve accuracy, and let their teams focus on more strategic tasks.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Sterling, VA
Founded
2024

Recently Posted Jobs

Explore more opportunities at Neuroscale AI

See more jobs