GTM Engineer, Sift
$140-180k
+ Equity + Bonus
More information about location
2 days a week in office
Unified observability for modern hardware
Open for applications
Unified observability for modern hardware
21-100 employees
Open for applications
$140-180k
+ Equity + Bonus
More information about location
2 days a week in office
21-100 employees
Company mission
To provide the tools that engineering teams need to efficiently manage hardware data and build the machines of the future.
Role
Who you are
- You write Python: You know Python well enough to build, debug, and own your own scripts and pipelines without help. You are comfortable with APIs, data manipulation, and working in a GitHub repo. You can read someone else's code and improve it
- You have worked with vector databases: You understand how embedding-based retrieval works and have built or maintained a RAG pipeline in production. You know how to chunk documents, choose an embedding model, evaluate retrieval quality, and debug when the wrong context comes back. Experience with Pinecone, Weaviate, pgvector, or similar is expected
- You have shipped real automation: Not configured a Zapier template. Built a system with inputs, outputs, failure handling, and real users depending on it. You can walk through exactly what you built, what broke, and how you fixed it
- You build with AI in production: You understand prompt engineering, API integration, and output validation. You know what AI is good at and where it fails. You have built workflows where the AI output feeds into something real, and you know how to make that reliable
- You know the GTM context: You understand what a BDR needs to find a good lead, what slows down a sales cycle, and what makes a piece of enablement actually useful in a deal. You have worked near a marketing or revenue team before and do not need the basics explained
- You are self-sufficient: You can go from a vague idea to a working prototype without a spec document or a dedicated engineering team. You ask the right questions, fill in the gaps, and ship
- You work well with non-technical teammates: You can explain what you are building and why it matters without making people feel lost. You listen before you build and check in before you assume
- You are curious and current: You follow the AI tooling space closely, bring new ideas to the team, and have opinions about what is worth using and what is hype
What the job involves
- Sift is hiring a builder at the intersection of AI, automation, and go-to-market execution
- Our platform is trusted by the most demanding engineering teams in aerospace, defense, energy storage, and robotics
- The people buying and using Sift move fast, operate in high-stakes environments, and expect the tools around them to keep up
- As our GTM motion scales, we need someone who can close the gap between our best ideas and what is actually running in production
- Someone who can take a whiteboard full of AI use cases, help prioritize, build a plan, and ship them
- Someone who treats the marketing and sales stack the same way an engineer treats a technical system: with rigor, curiosity, and a bias toward outcomes
- This is not a strategy role
- It is a building role
- You will build the AI and automation infrastructure that powers how Sift finds, engages, and converts customers
- From outreach signal pipelines and competitive intelligence systems to sales enablement tools and inbound automation, you will architect and build the systems that make the GTM team faster and sharper without adding headcount
- You will be the technical backbone of a marketing team that has already shipped AI in production and is ready to push further
- You will partner closely with marketing, ops, sales, and leadership to turn ideas into working systems
- You will bring structure to ambiguity, ship things that work, and improve them when they do not
- Architect and Build AI-Powered GTM Systems: Design and ship automation pipelines across outreach, competitive intel, sales enablement, inbound, events, content, and reporting. Own the AI infrastructure and code that makes the GTM team faster and more precise
- Write and Maintain Production Code: Build and own Python scripts, APIs, and integrations that connect data sources, AI models, and GTM tools into reliable workflows. Push and maintain work in GitHub. Document what you build so others can understand and extend it. This includes building and maintaining the vector database infrastructure that powers Sift's GTM AI Operating System, from ingestion pipelines to embedding models to retrieval logic
- Lead AI Workflow Development: Translate ideas from the team into working systems. Know when to use an AI model, when to use a rule, and when to use nothing at all. Build systems where AI output is reliable enough to trust in production
- Build and Own the Knowledge Infrastructure: Design and maintain the vector database that stores Sift's institutional knowledge as embeddings for GTM. Own the ingestion pipelines that pull from various data sources. Define chunking strategies, embedding models, and retrieval logic that make the system accurate and fast
- Contribute to the GTM Tech Stack: Collaborate with Ops to manage integrations across Slack, HubSpot, Clay, and other marketing tools in our stack. Keep systems clean, documented, and scalable as the business grows
- Collaborate Across Marketing and Sales: Work directly with the marketing team and BDRs to understand workflow bottlenecks, identify automation opportunities, and ship solutions that actually get used
- Drive the AI Roadmap: Help prioritize and sequence what to build next. Maintain a clear view of what is in production, what is in progress, and what is next. Surface tradeoffs and bring recommendations to leadership
- Maintain and Improve What You Ship: Build systems designed to last. Monitor pipeline performance, catch failures before the team does, and improve workflows as needs change or data quality shifts
Our take
Sift develops tools to accelerate and ensure the reliability of complex machines. Its platform processes hardware sensor data, providing automated analysis and detailed reports to identify and explain potential issues. This enables users in aviation, defense, energy and transportation to enhance system reliability and comply with regulatory requirements more efficiently.
The platform automates manual data review, which both enhances reliability and speeds up development. Customers like Astranis and Parallel Systems use Sift's observability stack to turn sensor data into actionable insights, which would have likely remained undiscovered when using other systems.
With several rounds of funding to its name, Sift is poised to expand its manufacturing automation suite to integrate sensor data with manufacturing information. This will enable it to assist with anomaly detection and performance analysis. It is also making advancements with AI integration for regulatory compliance, which sets it up as a key innovator in the space.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 3 rounds)
Mar 2026
$42m
SERIES B
Jun 2024
$17.5m
SERIES A
Total funding: $67m
Company benefits
- Unlimited PTO
- Free lunch, snacks, & coffee
- Top-tier health insurance: Medical, Vision, & Dental
Company HQ
El Segundo, CA
Leadership
Karthik Gollapudi
(CEO)Previously a Dragon Flight Software Lead at Spacex and a Full-Stack Engineer at Information Sciences Institute.
Austin Spiegel
(CTO)Previously a Software Engineering Manager at Riot Games. Prior to that, they worked at SpaceX in various Software Engineering roles.
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