Distinguished Engineer, Investment Systems

Posted One Month Ago
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Boston, MA, USA
Hybrid
200K-210K Annually
Expert/Leader
Fintech • Financial Services
The Role
Architect and deliver scalable private markets investment systems and advanced AI solutions. Lead end-to-end feature design, build production-grade LLM/RAG/agentic systems, mentor engineering teams, set standards for software, data, and AI engineering, and partner across platform, data, and security teams to operationalize proprietary private markets data.
Summary Generated by Built In

Job Description Summary

For over forty years, HarbourVest has been home to a committed team of professionals with an entrepreneurial spirit and a desire to deliver impactful solutions to our clients and investing partners. As our global firm grows, we continue to add individuals who seek a collaborative, open-door culture that values diversity and innovative thinking.
 

In our collegial environment, that’s marked by low turnover and high energy, you’ll be inspired to grow and thrive. Here, you will be encouraged to build on your strengths and acquire new skills and experiences.
 

We are committed to fostering an environment of inclusion that promotes mutual respect among all employees. Understanding and valuing these differences optimizes the potential of both the individual and the firm.
 

HarbourVest is an equal opportunity employer.
 

This position will be a hybrid work arrangement. You will receive 18 remote workdays per quarter to use at your discretion, subject to manager approval. For example, you may choose to work in the office 4 days per week and take one remote day weekly (typically 13 weeks per quarter), leaving 5 additional remote days to be used as needed.
 

Our Investment Platforms group is seeking a Distinguished Engineer to architect and guide our technical teams, to lead the design, delivery and long-term evolution of our private equity and private credit front office applications. This is a senior technical leadership role for someone who sets architectural direction and stays close to the code. You will guide how we build scalable financial technology systems and modern AI features. These features support our investment staff's decisions and improve engineering standards across all teams you impact. A core part of this role is crafting and delivering distributed financial technology solutions. You will modernize them using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic systems. These solutions will be put into production using our proprietary private markets data.

This hybrid position spans both application development and artificial intelligence development, requiring equal depth in platform architecture and applied AI

The ideal candidate is:
  • A technical leader who can provide architectural mentorship and influence teams without relying solely on formal authority

  • A self-starter with a love for technology, software application delivery, AI/ML, and mathematical applications

  • Experienced in taking generative AI solutions from prototype to reliable, production-grade systems

  • Equipped with excellent interpersonal skills to work well across multiple teams

  • Possessed strong analytical, organizational, and problem-solving skills as well as with outstanding attention to detail

  • Passionate about building tools to enable private and financial investment systems
     

What you will do:
  • Be responsible for the technical architecture for our investment systems, translating investment department needs into scalable, maintainable solutions

  • Lead features end to end design, code, run, and maintain pipelines, transformations, views, and test suites for applications and data validation

  • Establish engineering standards and provide mentorship to team members on software, data, and AI engineering practices

  • Build and deliver sophisticated AI technologies, LLM-powered applications, RAG pipelines, and autonomous and human-in-the-loop agents grounded in HarbourVest’s proprietary data

  • Apply AI across the SDLC, using AI-assisted development, testing, and code review to accelerate delivery and quality

  • Serve as a technical point of reference, reviewing designs and working with the firm’s Architecture Review Board to champion responsible engineering and AI standards for investment technology solutions

  • Partner with our Platform Engineering and Quantitative Investment Science teams to align technology strategies, optimize platform capabilities, and drive investment platforms business outcomes.
     

What you bring:

Leadership & Domain Expertise

  • This is a hands-on, code-first role. You'll write production code regularly, and your architectural decisions will grow directly out of that hands-on experience.

  • Distinguished Engineer-level experience architecting and leading implementation of large-scale systems for investment platforms and analytics engineering teams in investment management

  • Set engineering standards and mentor team members on software, infra, security, data, and AI engineering practices

  • Partner with Data, DevOps, Security, Infrastructure, and Application Development teams to integrate automated deployment and testing.

  • Act as a technical point of reference by reviewing builds, resolving complex problems, and championing engineering and responsible-AI procedures

  • Deep understanding of data as a strategic asset, treating data quality, structure, and governance as core to the role, not a downstream concern.

  • Extensive experience with private equity datasets, a delivery-focused, entrepreneurial mindset, and a track record of shipping software projects optimally to production are critical
     

Core Engineering Skills
  • Proficient in Python or Java and skilled in full-stack development using TypeScript, Node with experience in CI/CD pipelines. Python is preferred

  • Experienced in developing scalable FastAPI-based microservices maximising GraphQL and gRPC

  • Strong experience in data modeling, engineering, ETL/ELT frameworks, data quality and analytics using Snowflake or equivalent cloud warehouses

  • Experience with modern real-time and streaming data technologies (such as Apache Kafka, Azure Event Hubs or cloud-native event streaming platforms)

  • Expertise in building Docker or Kubernetes (AKS or EKS) containerized applications

  • Experience applying AI throughout the software development lifecycle for coding, validation, and code assessment with tools such as GitHub Copilot, Codex, or Claude Code

  • Experience building and deploying production systems on major cloud platforms (AWS, Azure, or GCP) would be advantageous
     

AI Engineering:
  • Practical experience developing tool-integrated agentic systems using the Model Context Protocol (MCP) and frameworks such as FastMCP

  • Practical experience developing and launching LLM solutions, RAG architectures and agentic workflows

  • Experience working 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 (e.g., LangGraph, AutoGen, CrewAI, or comparable) and human-in-the-loop patterns for high-stakes decision workflows

  • Experience architecting end-to-end document ingestion pipelines, including intake, OCR, layout-aware parsing, and normalization of PDFs, Word, Excel, and scanned files, with solutions including Azure Document Intelligence or LlamaParse etc

  • Deep hands-on expertise building custom extraction logic with lower-level libraries (e.g., Tesseract, Docling, PyMuPDF, Camelot, Tabula)

  • Experience fine-tuning LLMs for domain-specific extraction tasks and integrating agentic AI workflows to automate and orchestrate extraction, validation, and structuring pipelines
     

Nice to have skills:
  • Experience with DBT, pipeline orchestration tools such as Dagster or Airflow, and Azure data tooling.

  • Exposure to Azure OpenAI, Azure AI Foundry / AI services, or comparable cloud AI platforms is preferred

  • Knowledge of financial markets, investment systems, or private markets (private equity, private credit) is a plus.

  • Experience with simulation-based and probabilistic modeling techniques (e.g., 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
     

Education Preferred
  • Bachelor of Science (B.S.) or equivalent experience

  • Master of Science (M.S.) or equivalent experience
     

Preferred Qualifications
  • 12+ years of software Engineering and delivery experience preferred

  • 5+ years of technical leadership experience (as a Distinguished Engineer, technical lead, or hands-on engineering director)
     

#LI-Hybrid

Base Salary Range

$200,000.00 - $210,000.00

This USD base salary range represents only one component of total compensation for this role and is provided in accordance with local requirements. This role is eligible for a discretionary annual bonus, which is determined based on individual and overall firm performance. In addition to salary and bonus eligibility, total compensation may include participation in long-term reward programs (typically for more senior-level roles). We also offer a comprehensive total rewards package that may include retirement contributions, health insurance, income protection, paid time off and leave benefits as well as well-being programs. Our total rewards offerings are influenced by several business factors, and eligibility for certain components will vary by position and geography. Please note the posted ranges do not apply outside the U.S. and should not be converted to other currencies as a proxy for compensation in other countries.

Skills Required

  • Hands-on production coding and regular contribution to codebase
  • Distinguished Engineer-level experience architecting and leading large-scale investment platform systems
  • Proficient in Python or Java
  • Full-stack development experience using TypeScript and Node and familiarity with CI/CD pipelines
  • Experience developing FastAPI-based microservices and using GraphQL and gRPC
  • Strong experience in data modeling, ETL/ELT, data quality and analytics using Snowflake or equivalent
  • Experience with real-time/streaming technologies (Apache Kafka, Azure Event Hubs, or equivalent)
  • Expertise building Docker and Kubernetes (AKS or EKS) containerized applications
  • Practical experience building and launching LLM solutions, RAG architectures, and agentic workflows
  • Experience with OpenAI, Anthropic, or comparable language-model platforms and fine-tuning LLMs
  • Practical experience developing tool-integrated agentic systems using the Model Context Protocol (MCP) and frameworks such as FastMCP
  • Hands-on experience designing autonomous and multi-agent architectures and using agent orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI)
  • Experience building end-to-end document ingestion pipelines including OCR, layout-aware parsing, normalization (Azure Document Intelligence, LlamaParse, etc.)
  • Hands-on expertise with lower-level extraction libraries (Tesseract, Docling, PyMuPDF, Camelot, Tabula)
  • Experience applying AI across the SDLC with developer-assist tools (GitHub Copilot, Codex, Claude Code)
  • Deep understanding of data governance, data quality, and treating data as a strategic asset
  • Extensive experience with private equity or private credit datasets and delivering production software in investment management
  • Experience deploying production systems on major cloud platforms (AWS, Azure, or GCP)
  • Familiarity with DBT, pipeline orchestration tools (Dagster or Airflow), and Azure data tooling
  • Experience with Azure OpenAI, Azure AI Foundry or comparable cloud AI platforms
  • Bachelor's degree (B.S.) or equivalent experience; Master's preferred
  • 12+ years software engineering experience and 5+ years technical leadership experience preferred

HarbourVest Partners Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about HarbourVest Partners and has not been reviewed or approved by HarbourVest Partners.

  • Strong & Reliable Incentives — Incentives are portrayed as strong in certain teams and senior roles, with high bonus potential contributing meaningfully to total compensation. Overall packages can feel solid where variable pay is emphasized.
  • Healthcare Strength — Benefits are described as comprehensive, including medical, dental, vision, disability, life insurance, EAP, wellness programs, and fitness reimbursement. U.S. coverage explicitly includes domestic partners.
  • Parental & Family Support — Offerings include paid parental leave, adoption assistance, bereavement leave, paid volunteer time, and U.S. emergency back‑up childcare. These supports are positioned as competitive for the sector.

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The Company
HQ: Boston, MA
904 Employees
Year Founded: 1982

What We Do

HarbourVest is an independent, global private markets firm with 40 years of experience and more than $92 billion assets under management as of December 31, 2021. Our interwoven platform provides clients access to global primary funds, secondary transactions, direct co-investments, real assets and infrastructure, and private credit.

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