Engineering Manager, Data & AI

Venture-backed AI technology startup in the construction technology space is looking to add an Engineering Manager, Data & AI to its growing team in McLean Virginia (hybrid, 3 days onsite per week). This is an opportunity to lead a small team of 4–5 software engineers while remaining hands-on in building the data pipelines and AI-powered systems that transform complex construction documents, specifications, bid packages, and emails into structured, actionable intelligence.

The ideal candidate is a pragmatic, hands-on engineering leader with a strong full-stack software development background, deep PostgreSQL experience, and a track record of building reliable production systems. This person will help shape the technical direction of the platform, improve engineering quality, and work closely with product and company leadership to turn complex data and AI challenges into scalable customer-facing solutions.

Targeting:

• 7–10+ years of software engineering experience, with strong hands-on expertise in TypeScript, React, Python, Node.js or similar modern stack.
• Experience managing or tech-leading a small engineering team while continuing to write code and contribute to technical decisions.
• Deep experience with PostgreSQL, including data modeling, query optimization, schema design, and working with large tables.
• Experience building and operating production data pipelines and asynchronous background jobs, including retries, idempotency, backfills, and failure recovery.
• Experience building systems that ingest, process, and extract structured information from unstructured or semi-structured data, such as documents, PDFs, specifications, and emails.
• Hands-on experience integrating LLMs into production applications, ideally including prompt engineering, evaluation frameworks, tracing, prompt versioning, and monitoring model accuracy and cost.
• Experience designing APIs, system architecture, and reliable backend services that support customer-facing applications.

Nice to Have:

• Experience with data orchestration tools such as Dagster, DBT and/or Airflow.
• Familiarity with LLM observability and evaluation tools such as LangSmith, Langfuse, or MLflow.
• Experience building AI-powered document processing, NLP, information extraction, or data enrichment systems.
• Experience with AWS, cloud infrastructure, CI/CD, infrastructure as code, and production monitoring.
• Background working in a venture-backed startup, high-growth technology company, or vertical SaaS environment.
• Experience building data-intensive applications that integrate with external systems, APIs, and customer workflows.
• Familiarity with construction technology, HVAC, manufacturing, logistics, document management or other complex, data-heavy industries.

Benefits:

• Competitive compensation package with meaningful equity
• Flexible working hours and a hybrid work environment
• Education and certification reimbursement
• Paid holidays, vacation, and sick leave
• 401(k) with employer match