Tech Lead Manager, Context Engineering & Data Memory

Profound; San Francisco (CA); On-site; USD 230,000 - 275,000; Full time

Benefits offered by this job

Equity

Benefits package

Job summary

Profound is seeking a Tech Lead Manager to shape the Context team in San Francisco, balancing technical leadership with people management. You will guide architecture, data retrieval quality, and integration strategies while growing a small engineering team.

You will also write code, review PRs, and own critical decisions, collaborating with product and sales engineering to ensure secure, scalable data access for our AI marketing platform.

Qualifications

• 7+ years of backend engineering experience, with at least 2 years managing or tech-leading a team.
• Strong Python. This is the language the team lives in
• Rust is strongly preferred. Parts of this system are performance and cost sensitive enough to justify it, and we expect that surface to grow
• Hands-on experience building search or retrieval systems in production: embeddings, vector stores, hybrid search, reranking, and chunking strategies, along with an honest view of where each one stops helping
• Experience integrating with third-party APIs at scale, including OAuth, token refresh, rate limits, and the operational reality of connectors that break on someone else's schedule
• Experience with data synchronization and pipeline correctness: incremental sync, idempotency, backfills, and reconciliation
• Strong Postgres skills; you can reason about indexes, query plans, multi-tenant data models, and migrations without reaching for a tutorial
• Experience hiring senior ICs and giving direct, useful feedback
• Comfortable being an IC contributor on the team you manage; we don't want a manager who has stopped writing code
• Experience with knowledge graphs or entity resolution at scale
• Experience building memory systems or context management for LLM agents, including context budgeting and retrieval tuning against real workloads
• Familiarity with MCP as both a server and a client implementer
• Experience with high-volume event ingestion and streaming systems
• Background at a B2B SaaS company that sold to enterprise, where customer data handling passed a real security review (SOC 2, ISO 27001, CMEK, private networking)
• A track record of building evaluation harnesses for non-deterministic systems

Responsibilities

• Lead the Context roadmap, partnering with the CTO, Head of Engineering, and product leadership on priorities
• Hire and develop a team of 4 to 8 engineers, including running interview loops, calibrating performance, and setting expectations clearly
• Drive technical decisions on hard problems: retrieval quality and how we measure it, graph and memory schemas that survive contact with real customer data, sync architectures that stay correct under partial failure, and an integration framework that makes the tenth connector cheaper to build than the first
• Own retrieval quality as a measurable product surface, with evals that catch regressions before customers do
• Ship code yourself on the highest-leverage parts of the system
• Be the engineering point of contact when a customer's integration breaks, their data goes stale, or an agent retrieves the wrong thing
• Represent Context in conversations with product, sales engineering, and the executive team when data access, freshness, or security commitments are on the line
• Partner closely with the teams building our agent products, who are your primary internal customers

Skills

Backend engineering

Team leadership

Python

Rust

Search/retrieval systems

OAuth/API integration

PostgreSQL

Data pipelines

Distributed systems

Tools

Git

Docker

Kubernetes

Job description

Profound is seeking a Tech Lead Manager to shape the Context team in San Francisco, balancing technical leadership with people management. You will guide architecture, data retrieval quality, and integration strategies while growing a small engineering team.

You will also write code, review PRs, and own critical decisions, collaborating with product and sales engineering to ensure secure, scalable data access for our AI marketing platform.