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HarbourVest

Global private markets investment manager

Distinguished Engineer - Investment Systems

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeBoston, MA, USA

About the Job

Requirements

  • Distinguished Engineer-level experience architecting and leading implementation of large-scale systems for investment platforms and analytics engineering teams in investment management.
  • Proficiency in Python or Java and full-stack development using TypeScript and Node, with experience in continuous integration and continuous delivery pipelines; Python is preferred.
  • Experience developing scalable FastAPI-based microservices and using GraphQL and gRPC.
  • Strong experience in data modeling, data engineering, ETL/ELT frameworks, data quality, and analytics using Snowflake or equivalent cloud data warehouses.
  • Experience with modern real-time and streaming data technologies such as Apache Kafka, Azure Event Hubs, or cloud-native event streaming platforms.
  • Expertise building containerized applications with Docker or Kubernetes (AKS or EKS).
  • Experience applying AI throughout the software development lifecycle for coding, validation, and code assessment using tools such as GitHub Copilot, Codex, or Claude Code.
  • Practical experience developing tool-integrated agentic systems using the Model Context Protocol and frameworks such as FastMCP.
  • Practical experience developing and launching large language model solutions, retrieval-augmented generation architectures, and agentic workflows.
  • Experience with extensive language understanding models, including platforms such as OpenAI, Anthropic, or open-source models.
  • Hands-on experience designing autonomous and multi-agent architectures, including task planning, tool use, memory, and multi-step reasoning, using agent orchestration frameworks such as LangGraph, AutoGen, CrewAI, or comparable tools, and human-in-the-loop patterns for high-stakes decision workflows.
  • Experience architecting end-to-end document ingestion pipelines, including intake, optical character recognition, layout-aware parsing, and normalization of PDF, Word, Excel, and scanned files, with solutions such as Azure Document Intelligence or LlamaParse.
  • Deep hands-on expertise building custom extraction logic with lower-level libraries such as Tesseract, Docling, PyMuPDF, Camelot, and Tabula.
  • Experience fine-tuning large language models for domain-specific extraction tasks and integrating agentic AI workflows to automate and orchestrate extraction, validation, and structuring pipelines.
  • Deep understanding of data as a strategic asset, treating data quality, structure, and governance as core responsibilities.
  • Extensive experience with private equity datasets and a track record of delivering software projects to production.
  • Experience with private equity and private credit datasets, investment management, and analytics engineering.
  • Experience with 12+ years of software engineering and delivery is preferred; 5+ years of technical leadership experience as a Distinguished Engineer, technical lead, or hands-on engineering director is preferred.

Responsibilities

  • Own the technical architecture for investment systems, translating investment department needs into scalable, maintainable solutions.
  • Lead features end to end by designing, coding, running, and maintaining pipelines, transformations, views, and test suites for applications and data validation.
  • Establish engineering standards and mentor team members on software, data, and AI engineering practices.
  • Build and deliver AI technologies, large-language-model-powered applications, retrieval-augmented generation pipelines, and autonomous and human-in-the-loop agents grounded in proprietary data.
  • Apply AI across the software development lifecycle, using AI-assisted development, testing, and code review to accelerate delivery and quality.
  • Serve as a technical point of reference, review designs, and work with the Architecture Review Board to champion responsible engineering and AI standards for investment technology solutions.
  • Partner with Platform Engineering and Quantitative Investment Science teams to align technology strategies, optimize platform capabilities, and drive investment platform business outcomes.
  • Partner with Data, DevOps, Security, Infrastructure, and Application Development teams to integrate automated deployment and testing.
  • Review builds, resolve complex problems, and champion engineering and responsible-AI procedures.
  • Write production code regularly and base architectural decisions on hands-on experience.
  • Architect and guide technical teams in the design, delivery, and long-term evolution of private equity and private credit front-office applications.
  • Modernize distributed financial technology solutions using large language models, retrieval-augmented generation, and agentic systems, deploying these solutions into production using proprietary private markets data.

Desired Qualifications

  • Experience building and deploying production systems on major cloud platforms such as AWS, Azure, or GCP.
  • Experience with dbt, pipeline orchestration tools such as Dagster or Airflow, and Azure data tooling.
  • Exposure to Azure OpenAI, Azure AI Foundry, Azure AI services, or comparable cloud AI platforms.
  • Knowledge of financial markets, investment systems, or private markets, including private equity and private credit.
  • Experience with simulation-based and probabilistic modeling techniques such as Monte Carlo methods for forecasting, portfolio construction or allocation, and decision-support applications.
  • Hands-on experience building knowledge graphs, including entity and relationship extraction, entity resolution, and ontology or schema design.

About the Company

HarbourVest

Global private markets investment manager

HarbourVest Partners is a global private markets investment firm focusing on private equity through fund-of-funds, secondary investments, and direct co-investments in operating companies. It channels capital into private equity via commingled funds or customized separate accounts, spanning venture capital and leveraged buyouts. The firm differentiates itself with a globally scaled, integrated platform that combines multiple investment channels and flexible client structures. Its goal is to make private markets accessible to a wide range of investors by offering diverse, multi-channel private equity opportunities.

Company size
1,001-5,000
Company stage
Not listed
Total funding
$10.7B
Headquarters
Boston, MA
Founded
1982

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