Member of Technical Staff, TLM, Context Engineering

Profound is the fastest-growing AI marketing platform, used by 15% of the Fortune 500 including Comcast, Estée Lauder, and Walmart, and innovators like Ramp, MongoDB, and Figma. It is where marketing teams do the work: research, briefs, content, campaigns, reporting, all in one place, alongside agents that carry the load with them.

Built on 2B+ real user prompts and growing, Profound’s data shows you what people ask AI and what the models say back. Profound's AI Marketer joins that data with deep context about our customers to find the opportunities worth acting on, and then puts agents to work: automating reporting, drafting content, auditing pages for readability, running competitive research. It measures what works and gets better every day.

We are hiring a Tech Lead Manager to build and lead our Context team in San Francisco. Context owns everything Profound knows about a customer and everything our agents reach for when they do work. Every integration a customer connects, every document and page we ingest, every entity we resolve, and every piece of durable memory an agent carries between sessions runs through this team. If our agents are the hands, Context is the memory and the senses. The quality of what we ship is bounded by the quality of the context we retrieve.

This is a hybrid role. You'll spend roughly half your time on technical leadership and architecture, and half on people management, hiring, and execution. We expect you to write code, review PRs, and be in the details on critical decisions. We also expect you to grow engineers, run a tight planning process, and own outcomes for the team.

The Context team owns the integration service (the shared substrate for connecting to third-party systems: OAuth flows and token lifecycle, API key management, MCP servers and clients, credential storage and rotation, webhook ingestion, and per-provider rate limiting and backoff); the integration catalog itself (CMS platforms, analytics and search consoles, CRMs, document stores, support desks, and commerce systems, each with its own auth model, pagination quirks, and failure modes); knowledge base storage and retrieval (ingestion and chunking, embeddings, hybrid keyword and vector search, reranking, freshness, and strict tenant isolation across a store handling billions of documents); data synchronization (incremental sync, backfills, change detection, deduplication, conflict resolution, and the observability that tells us a customer's data is current before they notice it isn't); and context management (the knowledge graph that resolves brands, products, competitors, topics, and pages into a coherent model of a customer's world, plus the long-term memory service that lets agents accumulate and reuse what they learn).

What you'll do

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

Who you are

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

Nice to have:

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

Location

This is an on-site role based in our SF office, designed for builders who thrive on speed, iteration, and meaningful impact.

For this role, the expected base salary range is $230,000 to $275,000, depending on experience. Profound's total compensation package includes base salary, equity, and a full range of benefits and perks. Final compensation will depend on factors such as your skills, experience, qualifications, and location, and will be determined during the interview process. Our recruiting team will share more details about the full compensation package and benefits as you move through hiring.

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