Data & AI Engineer (AI)

Location: Washington, D.C. or New York, NY; in-office 4 days per week

Base salary: $160,000–$180,000 per year, plus potential discretionary annual incentive and benefits.

Company

hirify.global operates across private markets, bringing together capital, ideas, and companies to support growth and investor performance.

What you will do

• Build and operate AI-ready pipelines for embedding generation, chunking, indexing, refresh workflows, and enterprise data retrieval.
• Implement RAG components, vector store integrations, hybrid search, re-ranking, grounding logic, and safe agent and copilot tool interfaces.
• Design and maintain production-grade ELT, streaming, transformation, semantic, and analytical data pipelines using dbt, Fivetran, Snowflake, Python, and SQL.
• Develop reusable data products, semantic models, data contracts, contextual metadata, and discovery tooling for human and AI consumers.
• Implement data quality, lineage, observability, logging, evaluation, monitoring, access controls, and AI trust mechanisms.
• Collaborate with architects, data scientists, AI engineers, governance specialists, and domain teams; mentor junior data engineers and analysts.

Requirements

• Bachelor’s degree required; computer science, data engineering, information systems, or a related concentration preferred. A master’s degree and relevant certifications are preferred.
• 6+ years of relevant technical experience, including 1–2 years of hands-on production experience building generative AI or AI/ML systems.
• Production experience with RAG pipelines, vector stores, embedding workflows, retrieval, grounding, semantic components, structured tool use, agents, or LLM applications.
• Strong Python and SQL skills, with working knowledge of distributed processing frameworks such as Spark.
• Deep experience with modern data stacks including dbt, Fivetran, and Snowflake in AWS-based environments.
• Experience with AI platforms and tools such as AWS Bedrock, Databricks ML, Snowflake Cortex, OpenAI or Anthropic APIs, LangChain or LlamaIndex, MLflow, and vector databases; financial services experience is preferred.

Nice to have

• Palantir experience.
• Experience with federated data operating models and complex, regulated enterprise environments.
• Relevant cloud, data engineering, analytics, or AI/ML certifications.

Culture & Benefits

• Work within a federated enterprise technology and data organization supporting firm-wide investment, portfolio, investor relations, and corporate initiatives.
• Partner across architecture, data science, AI engineering, governance, and domain teams.
• Retirement benefits, health insurance, life and disability insurance, paid time off, and paid holidays.
• Family planning benefits and wellness programs.
• Potential eligibility for an annual discretionary incentive program based on individual and organizational performance.