About this opportunity
Curate Partners lists this Lead Engineer, Investment Systems opportunity in boston, Massachusetts. Review the employer’s description below for duties, qualifications and application requirements.
Job description
This role cannot sponsor - open to USC or GC
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
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)
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Worksite address
boston, MA, 02298, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.