Neuroscale AI

• Perform a deep audit of the current QA setup across ARBI, Athena, frontend flows, backend services, APIs, data workflows, integrations, AI pipelines, and release processes. • Define a company-wide QA strategy across short-term stabilization, mid-term automation, and long-term quality engineering maturity. • Design a scalable test architecture using test pyramid principles, shift-left testing, smoke testing, regression testing, release gates, exploratory testing, and risk-based coverage. • Define clear QA responsibilities between developers, QA, product, design, customer success, and release owners. • Establish a practical quality operating rhythm: test plans, release checklists, defect triage, severity definitions, sign-off workflows, and quality metrics. • Validate implementation against requirements, designs, copy, acceptance criteria, user stories, and customer-specific workflows. • Test UI, UX, business logic, responsiveness, edge cases, error states, empty states, loading states, accessibility, and validation messages. • Perform exploratory, smoke, regression, and release-candidate testing before launches. • Validate recruiter workflows including candidate search, matching, scoring, resume parsing, outreach sequencing, scheduling, recruiter dashboards, candidate profiles, and ATS/CRM-style workflows. • Validate Athena workflows including resume support, interview preparation, rubric-based feedback, candidate assistance, AI-generated recommendations, and user-facing guidance. • Take ownership of automated frontend, API, integration, and end-to-end test coverage using Cypress, Playwright, Pytest, Postman/Newman, or equivalent tools. • Create reliable automated regression suites for critical ARBI and Athena workflows, including authentication, permissions, candidate pipelines, analytics, notifications, integrations, and admin experiences. • Integrate tests deeply into CI/CD pipelines so failures are visible, actionable, and tied to release confidence. • Improve test reliability, execution speed, data setup, fixture management, and maintainability. • Validate robust REST APIs, Python/FastAPI services, backend business logic, asynchronous workflows, and data-processing pipelines. • Create API and integration test coverage for imports, exports, webhooks, permissions, search, scoring, candidate data, customer-specific configuration, and workflow automation. • Create clear, structured, reproducible bug reports with screenshots/videos, environment details, severity, expected behavior, actual behavior, impact, and reproduction steps. • Retest fixed issues, validate root-cause resolution, and prevent regressions.

• Close deals and build the brand that makes inbound deals the default. • Manage fast deal cycles across multiple customer types. • Build awareness of Neuroscale and Arbi. • Translate strategy into shipped experiments. • Surface amazing hires and turn them into stories for the market.

• Define and own the overall technical vision, platform architecture, and engineering roadmap in alignment with product strategy and company growth. • Lead, recruit, and scale a world-class engineering organization, including hiring standards, team design, mentorship, and technical culture. • Oversee the design, development, and reliability of Neuroscale's backend systems, agents, talent matching models, orchestration layers, APIs, data workflows, and ext. integrations. • Drive sound architectural choices across backend systems (such as TypeScript/NestJS and Python/FastAPI), frontend applications, and AI/ML infrastructure. • Establish and enforce engineering best practices across security, observability, testing, reliability, incident response, and documentation. • Build the operational foundation required for scale, including runbooks, deployment patterns, developer tooling, and health metrics for engineering performance. • Own the company's compliance and certification roadmap across enterprise trust requirements, including security and privacy frameworks. • Represent the company's technical strategy externally with customers, partners, analysts, investors, and research institutions.

• Design, build, and maintain scalable batch and streaming data pipelines that support Neuroscale AI's core platform • Build robust ingestion, transformation, enrichment, and indexing workflows across structured, semi-structured, and document-centric data • Develop and operate production-grade data systems using PostgreSQL, OpenSearch/Elasticsearch, AWS, and Python-based tooling • Design efficient data models, schemas, and storage patterns that support analytics, search, application workflows, and AI use cases • Build secure cloud-native data infrastructure using AWS services such as S3, Lambda, Glue, Kinesis, and IAM • Optimize PostgreSQL for advanced SQL workloads, replication, query performance, and data integrity • Design and manage search and retrieval pipelines in OpenSearch/Elasticsearch for high-speed, relevant access to data • Improve observability, lineage, testing, and reliability across the data platform • Automate infrastructure provisioning and environment management using Terraform or CloudFormation • Partner closely with backend, product, and AI teams to enable new data-driven capabilities and platform features • Help define engineering standards, data platform best practices, and operational playbooks as the company scales

• Design, build, and maintain robust backend systems that power Neuroscale AI’s core platform • Develop and scale REST APIs using Python and FastAPI • Build production-ready systems using PostgreSQL, Redis, OpenSearch, Celery, and Temporal • Architect and optimize systems that handle large-scale datasets and high-throughput backend workflows • Build, deploy, and maintain backend services on AWS • Own containerized deployments, CI/CD pipelines, and backend infrastructure reliability • Support integrations, data pipelines, workflow automation, and asynchronous processing systems • Help define backend architecture, engineering standards, observability, and performance practices • Work closely with product, AI, and frontend teams to deliver features that power B2B and B2C SaaS experiences • Mentor engineers and raise the bar on engineering quality, speed, and execution • Operate like an owner in a startup environment, balancing speed with sound engineering judgment • Contribute to AI-enabled engineering workflows and modern developer tooling, including tools such as Cursor and/or Claude Code

• Design, build, and scale Neuroscale’s partner-led go-to-market motion • Create a repeatable system that recruits, enables, and activates partners • Identify, recruit, and close high-impact partnerships with ATS, HRIS, and adjacent HR tech platforms • Drive co-marketing and co-selling motions with ecosystem partners • Recruit and enable VARs, SIs, and solution providers

• Design, build, and maintain backend services using TypeScript (preferably NestJS) • Develop and document robust REST and GraphQL APIs used by frontend and AI components • Work with PostgreSQL and Redis to manage structured and real-time data • Collaborate across teams to integrate AI pipelines, inference systems, and third-party APIs • Own backend performance, reliability, observability, and dev workflow improvements • Drive engineering excellence via clean code, code reviews, and strong documentation • Evolve authentication, authorization, and permissioning systems • Contribute to architecture decisions with a long-term view on scale and maintainability

• Own Arbi, Athena, and Aurora demos end to end, including discovery, tailored demo, objections, and next steps • Partner with Sales to align demo strategy to buyer pain points, technical requirements, and success criteria • Run demos independently for multiple buyer personas including recruiting, operations, leadership, and IT • Drive technical confidence during sales cycles and help advance deals toward signature • Lead technical validation during trials and POCs by defining success criteria, managing timelines, and removing blockers quickly • Troubleshoot issues and guide prospects through real world workflows • Support and validate common ATS integration patterns and deployment configurations • Own or co-own customer onboarding to ensure a smooth handoff from Sales and fast time to value • Lead training sessions, onboarding calls, office hours, and enablement initiatives • Create and maintain enablement materials, best practices, and usage guidance • Monitor usage and adoption to identify risks and expansion opportunities early • Support integrations with ATS platforms and related HR systems • Work hands on with APIs, webhooks, SSO or SAML, SCIM, data mappings, and CSV based workflows • Troubleshoot customer issues and coordinate with Engineering when deeper fixes are required • Act as the customer voice internally by gathering concerns, complaints, and feature gaps from customer interactions • Synthesize feedback into clear, actionable inputs for Product and Engineering • Build a tight feedback loop from customer calls to prioritized product and process improvements • Track and report on customer health signals including usage, satisfaction, risks, renewals, and expansion indicators • Help define and evolve customer success metrics as the company scales