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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive experience in building and operating production software with a strong focus on Python, backend services, and large-scale data pipelines. Capable of mentoring engineers and leading complex technical projects while ensuring alignment with product and data science teams.
Highest-signal resume keywords
Python ProgrammingProduction Software DevelopmentLarge-Scale Data PipelinesRetrieval-Augmented Generation (RAG)Access Control and Permissions Management
ATS Keywords
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Hard Skills
Production Software DevelopmentPython ProgrammingBackend ServicesAPIsLarge-Scale Data PipelinesRetrieval-Augmented Generation (RAG)EmbeddingsVector SearchContext ManagementMulti-Tenant Data Management
Soft Skills
Technical JudgmentMentoringCollaboration
Tools & Technologies
Search ToolsDocument Retrieval SystemsData RoomsVector Stores
Industry Keywords
M&A DocumentsDocument ManagementConfidential Document ProcessingHybrid Search
Tech Stack
Tools & technologiesPython
About the role
Key responsibilities & impact- Own retrieval for agents working on live deals
- Ground answers in the correct documents and data while balancing quality, speed, and cost
- Scale platform processing for large documents and data tables
- Shape and evolve agent context for increasingly complex deal workflows
- Build search tools that agents call, covering indexed and not-yet-indexed content
- Return trustworthy snippets, citations, and document locations
- Keep agent context aligned with data-room permissions and user access
- Determine when models may answer from retrieved context and when product checks are required
- Mentor engineers and set technical direction for retrieval across teams
- Partner closely with Product and Data Science while remaining hands-on with technical decisions
Requirements
What you’ll need- 6+ years of building and operating production software
- Record of leading complex technical work across teams
- Strong hands-on Python experience
- Experience with backend services, APIs, and large-scale data pipelines
- Experience with production LLM applications that depend on retrieval, including tool calling, RAG, embeddings, vector search, or context management
- Strong foundations in permissions, multi-tenant data, and access control on what an agent can retrieve
- Clear product and technical judgment, including balancing answer quality, latency, and cost
- Nice-to-have: long-running agent workflows that search or read documents
- Nice-to-have: vector store experience at production scale
- Nice-to-have: processing large confidential documents and data tables
- Nice-to-have: hybrid search, citations, and evaluation of retrieval quality
- Nice-to-have: virtual data rooms, M&A documents, or similar document-heavy work
- Nice-to-have: tool interfaces that expose search to an agent
Benefits
Comp & perks- Health insurance (medical, dental, vision)
- Retirement savings plan
- Paid time off
- Other employee benefits
- Potential eligibility for bonuses, commissions, or overtime if applicable
- Hybrid work with in-office collaboration on Mondays, Tuesdays, and Thursdays