Parspec

Full-stack Engineer

• Own the hardest cross-org technical problems
• Shape the technical strategy
• Ship code and own critical systems
• Set the standard for AI-augmented development
• Manage development across git worktrees
• Continuously improve development workflows
• Drive architectural evolution
• Ensure all systems meet quality standards
• Make leads better through collaboration
• Define best practices for AI-assisted development

Staff Engineer – Application Pod

Product Designer

• Own the design of product features from early discovery and concept development through detailed design and delivery with engineering.
• Translate complex workflows into intuitive interfaces and clear user flows.
• Work closely with Product and Engineering to iterate quickly and ship high-quality experiences.
• Produce high-quality interaction and visual design with strong attention to hierarchy, clarity, and usability.
• Communicate design decisions clearly through prototypes, documentation, and rationale.
• Collaborate with product and engineering teams to design and launch features—such as enhanced search interfaces and intuitive data visualization tools—that drive higher user engagement.

Senior Product Designer

Product Manager

• Lead scoped product initiatives from discovery through execution in partnership with Engineering and Design
• Develop a deep understanding of customer workflows through qualitative and quantitative research
• Define product requirements, user experiences, use cases, and success metrics
• Author clear product requirements, user stories, and decision documents to align cross-functional teams
• Ship product and feature improvements through rapid iteration, experimentation, and feedback

Product Management Intern

Machine Learning Engineer

• Lead the design and implementation of advanced Search, Ranking, and Recommendation systems
• Develop high-precision NLP and document extraction pipelines
• Research and implement novel deep learning architectures
• Develop, train, and deploy deep learning and machine learning models
• Collaborate with product managers and UX designers to integrate AI components into fully functional systems

Senior Machine Learning Engineer

AI Engineer

• Contribute to AI-driven initiatives, from problem framing through experimentation and implementation
• Build, prototype, evaluate, and iterate on models and AI-powered workflows used in customer-facing product features
• Partner with Senior Applied AI Engineers and Product Managers to translate real customer problems into clear technical approaches and tradeoffs
• Analyze structured and unstructured data (e.g., product specifications, documents, metadata) to improve model performance
• Document assumptions, results, and learnings to support cross-functional alignment and decision-making

Applied AI Engineer Intern

• Own the architecture for our hybrid search engine, blending keyword-based retrieval with dense vector embeddings to improve precision and recall.
• Design and scale personalization algorithms that suggest products based on project specs, historical data, and cross-catalog compatibility.
• Lead the fine-tuning of open-source and proprietary LLMs/encoders for specialized construction domain tasks, including NER and relationship extraction from complex documents.
• Architect and optimize our vector database strategy for high-concurrency retrieval and low-latency ranking.
• Work closely with product managers, UX designers, and business leadership to integrate AI components into fully functional systems.
• Participate in the complete product lifecycle from concept design to development, testing, and deployment.
• Build products that handle large data volumes efficiently while remaining highly scalable for new clients.
• Design end-to-end data and ML pipelines for seamless production integration and monitoring.
• Work with the leadership team on research efforts to explore cutting-edge technologies.
• Uphold a culture of excellence by maintaining high standards in code quality, innovation, and rigorous experimentation.

Staff Engineer – Applied ML, Search & Recommendations

Product Marketing

• Research and analyze different construction trades and customer segments to help refine Parspec’s Ideal Customer Profiles (ICPs)
• Map and define buying groups and personas within contractor and supplier organizations, including economic buyers, champions, and end users
• Analyze pipeline, customer, and product usage data to identify patterns in deal velocity, win rates, and expansion opportunities
• Build and maintain dashboards and reports to support Sales and Marketing performance tracking
• Support CRM data hygiene, including account structures, contact data, segmentation, and lifecycle stages
• Document and improve revenue processes across the funnel (lead → deal → customer)
• Assist with tooling, automation, and experimentation across CRM and sales systems
• Partner cross-functionally to answer ad-hoc analytical questions and unblock execution
• Translate insights into clear recommendations that inform GTM strategy and operational decisions

Strategic Go-To-Market Intern

Security Engineer

• Design and implement comprehensive cybersecurity measures, policies, guidelines, and processes for all applications, services, and cloud infrastructure components (e.g., AWS, GCP, Azure).
• Develop and maintain policies that incorporate early detection of security issues while adhering to industry best practices in cybersecurity.
• Collaborate with the engineering team to ensure secure DevOps practices are followed (e.g., SAST, DAST, SCA).
• Lead initiatives to foster a culture of secure coding by conducting training sessions on topics such as OWASP Top 10 Web and OWASP Top 10 AI.
• Build Parspec’s internal penetration testing function from the ground up by defining its scope and partnering with the engineering team for remediation efforts.
• Conduct regular manual security assessments and vulnerability scans for web applications, APIs, and cloud environments.
• Act as Incident Commander during security incidents by rallying team members to contain and resolve issues promptly.
• Monitor and analyze security events to provide timely responses and mitigation strategies.
• Assist with compliance efforts such as SOC2 audits and ensure adherence to relevant frameworks (e.g., ISO 27001, NIST).
• Collaborate on external engagements for cybersecurity projects while maintaining alignment with regulatory requirements.
• Implement and manage security tools such as firewalls, VPNs, intrusion detection/prevention systems (IDS/IPS), SIEM systems, endpoint protection solutions, and vulnerability management tools.
• Partner with development and DevOps teams to integrate security best practices into the software development lifecycle (SDLC).

Cybersecurity Engineer

Content Marketing Manager

• Develop, manage, and execute a content calendar across key channels (blog, e-books, whitepaper, LinkedIn, newsletters, etc.) aligned with marketing priorities
• Ensure content supports Parspec positioning, messaging, and pipeline objectives
• Collaborate cross-functionally with the CEO, demand generation, product marketing, and sales, to ensure content supports broader business goals
• Turn thought-leadership content (webinars, talks, interviews) into multiple assets, including: Short videos, Ebooks and downloadable guides, Blog articles, Email sequences, LinkedIn posts and carousels, etc
• Collaborate with the Demand Generation team to ensure content is effectively aligned with campaign goals across all channels (owned, earned, and paid).
• Write email campaigns and nurture sequences
• Develop content for syndication and partnerships
• Collaborate on gated content strategy and lead capture assets
• Support campaign messaging and asset creation
• Track and report on content KPIs tied to traffic, engagement and lead generation
• Analyze performance data and continuously optimize content strategy

SDET

• Own test strategy, automation, and reliability validation for Crawler, Platform, and Search services using Python, Go, and AWS tools.
• Design end-to-end automated testing frameworks for microservices, asynchronous data pipelines, integration, regression, and performance testing.
• Build synthetic and chaos testing frameworks to identify edge cases, performance bottlenecks, and data workflow issues in large-scale crawling systems.
• Collaborate with Platform engineers to instrument observability, alerting, and monitoring (AWS OpenSearch, Prometheus, Grafana, CloudWatch).
• Partner with Search engineers to validate query relevance, accuracy, latency, and performance SLAs.
• Introduce static analysis, CI/CD gate validation, and reproducible test environments to catch issues early.
• Create automated performance benchmarking tools to measure throughput, latency, and cost economics across distributed components.
• Contribute to internal QA frameworks for AI API evaluation, schema validation, and data consistency checks.
• Drive continuous improvement and quality ownership across mission-critical systems powering construction data intelligence.