Manager, CPE Data Engineering Lead (AI)

Location: Washington, DC, United States of America

Base salary: $140,000–$180,000 annually

Company

hirify.global invests in private markets and delivers performance for investors and portfolio companies.

What you will do

• Lead development and production delivery of LLM-powered applications, agents, MCP services, and integrations for investment, valuation, fund finance, and investor relations workflows.
• Define AI evaluation cases, regression suites, acceptance criteria, and release gates for accuracy, cost, latency, and traceability.
• Design security and governance controls including OAuth/OIDC, entitlement-based row-level security, tool guardrails, prompt-injection protection, and audit logging.
• Lead and mentor contract developers, data engineers, and QA; set technical direction, review designs and code, and remain hands-on.
• Maintain governed data models, metadata, lineage, data quality controls, and reliable pipelines supporting valuations, fund performance, and investor reporting.
• Own CI/CD, infrastructure as code, production support, incident response, modernization of legacy workloads, and communication with business stakeholders.

Requirements

• Bachelor’s degree required; a concentration in computer science, engineering, finance, economics, or another quantitative discipline is preferred.
• 7+ years of relevant experience in software engineering, data engineering, or technical analytics, including 3+ years building and operating production solutions used by business stakeholders.
• 2+ years leading engineering delivery, including backlog ownership, technical direction, coding standards, and developer or contractor reviews.
• Strong proficiency in Python and SQL, plus experience with C#/.NET or TypeScript.
• Production experience with LLM-powered applications, including tool use, agents, retrieval, structured outputs, and prompt and context design.
• Experience evaluating AI systems through test cases, regression suites, failure diagnosis, measured tuning, and validation against source data.
• Experience with a cloud data platform and transformation tooling such as Snowflake, Databricks, or Azure Synapse with dbt or Spark; Snowflake and dbt are strongly preferred.
• Experience with AWS or Azure, CI/CD such as GitHub Actions, and Terraform infrastructure as code.
• Knowledge of dimensional and semantic modeling, layered architectures, metadata, lineage, data quality, reconciliation, and security for AI and data systems.
• Required experience using AI coding assistants in a team setting with code review and guardrails, plus strong leadership, mentoring, and communication skills.

Nice to have

• Cloud, data platform, or AI certification such as AWS, Microsoft Azure, SnowPro, or dbt.
• Experience with MCP, agent frameworks, or tools and integrations for AI assistants.
• AWS experience with ECS, Lambda, or S3.
• Production support, incident management, root cause analysis, and remediation experience.
• Private equity, asset management, transaction advisory, or financial services data experience, including fund structures, deals, valuations, portfolio monitoring, and performance metrics.
• Power BI or similar reporting tools.

Culture & Benefits

• Full-time employment with retirement benefits, health, life, and disability insurance.
• Paid time off, paid holidays, family planning benefits, and wellness programs.
• Potential eligibility for an annual discretionary incentive program based on individual and organizational performance.
• Work involves collaboration with senior management, business stakeholders, Information Security, Compliance, Data Governance, and vendor delivery teams.