Our mission is simple and clear: we help organizations win more business by helping them craft better proposals in a fraction of the time.
Our solution combines the power of AI, your existing knowledge library and specialist features designed by bid-writers, for bid-writers, to ensure you have the competitive edge. An AutogenAI Language Engine will make your bid-writing team up to 8X more efficient, allow them to get to first draft in minutes rather than days and boost your win rates by up to 30%.
Our team is made up of dedicated specialists in procurement, bid writing, and machine learning, each one contributing to the exceptional solutions we deliver.
We believe that every organization is unique with its own specific needs and specifications. This is why we offer tailored solutions, with customizable options ranging from personalized language style to bespoke prompts.
We are proud to be one of the fastest growing generative AI companies out there. Our method works, and our results speak for themselves.
At AutogenAI, we understand that winning is the most crucial goal. It is through this lens that we deliver true value.
Our mission is simple and clear: we help organizations win more business by helping them craft better proposals in a fraction of the time.
Our solution combines the power of AI, your existing knowledge library and specialist features designed by bid-writers, for bid-writers, to ensure you have the competitive edge. An AutogenAI Language Engine will make your bid-writing team up to 8X more efficient, allow them to get to first draft in minutes rather than days and boost your win rates by up to 30%.
Our team is made up of dedicated specialists in procurement, bid writing, and machine learning, each one contributing to the exceptional solutions we deliver.
We believe that every organization is unique with its own specific needs and specifications. This is why we offer tailored solutions, with customizable options ranging from personalized language style to bespoke prompts.
We are proud to be one of the fastest growing generative AI companies out there. Our method works, and our results speak for themselves.
At AutogenAI, we understand that winning is the most crucial goal. It is through this lens that we deliver true value.
Product: AI platform that builds custom language engines to automate and accelerate proposal, grant, and RFP writing
Headquarters: New York City (offices in London and Brisbane)
Founders: Sean Williams and Raj Khaira
Recent funding: Series B announced Dec 6, 2023 (investors include Salesforce Ventures and Spark Capital)
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Company Overview
Problem Domain
Proposal, grant and RFP/bid writing for enterprises, government agencies and nonprofits
Founded
2022
Industry
Technology, Information and Internet
Funding Track Record
Series A- July 26, 2023
$22.3M
Series B- December 6, 2023
$39.5M
Reported to bring total investments to $65.3M
Investor Signal
“Backed by Blossom Capital, Spark Capital, and Salesforce Ventures”
Founders
What we do
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Strong Hands-On Analytics Capability: You are comfortable owning analytics delivery end-to-end, from raw data through to dashboards and executive-level insights
Product-Minded Thinking: You focus on metrics that reflect real user and business value, and can help teams define what success looks like before work begins
Analytics Engineering Fluency: You can write and review SQL, dbt models, and Python, and understand data pipelines well enough to ensure correctness and scalability
Clear Communication & Judgment: You can challenge assumptions, explain trade-offs, and make complex data understandable to non-technical stakeholders
Operational Data Leadership: You will have experience of balancing delivery across multiple stakeholders, with strong hands-on involvement to ensure quality, focus, and momentum. You may have some experience managing people or leading a small team
Experience: Several years spent in analytics, data analytics, or analytics engineering roles, including hands-on delivery and stakeholder-facing work
Industry Knowledge: Experience working in SaaS or product-led technology environments
Technical Skills:
Advanced SQL and dbt
Data modelling (preferably familiar with Kimball approach)
Redshift or similar cloud data warehouses
Power BI dashboard design and modelling
Python for analytics and code review
AWS familiarity (Glue, ECS, Docker, Lambda)
Alerting & Monitoring
Education: Degree in a quantitative, technical, or related discipline, or equivalent practical experience
Product Analytics: Experience defining tracking schemas, product KPIs, and analytics frameworks in collaboration with Product and Engineering
Business Analytics: Experience translating business questions into clear metrics, analysis, and insights — with the judgment to focus on what drives real decision-making, not just what is technically measurable
What the job involves
As Senior Analytics Engineer at AutogenAI, you will own analytics delivery across the business, ensuring data is trusted, used, and directly informs decision-making
You’ll work end-to-end across metrics, models, and dashboards, translating complex data into clear and decision ready insights for product, commercial, and leadership teams
AutogenAI has a modern data stack already in place, including a cloud data warehouse, analytics engineering layer, and semantic models supporting core business and product use cases
In this role you’ll maximise the value of those foundations - sharpening metrics, improving adoption, extending models where needed, and making analytics a dependable input into day-to-day and executive decisions
This is a hands-on role where you’ll spend a significant proportion of your time writing SQL and dbt models and building Power BI dashboards the business relies on weekly
You’ll work closely with Product, Engineering, Commercial, and Finance, and play a key role in shaping how analytics evolves as the company scales. You’ll have one direct report from day 1, and this is a great opportunity for those looking to grow into leadership in time
Hands-On Analytics Delivery: Design, build, and maintain core analytics outputs, including Power BI dashboards, ad-hoc analysis, and recurring reporting used by product, commercial, and leadership teams
KPI & Metrics Ownership: Define, document, and own company and product KPIs, ensuring consistency, clarity, and trust in how performance is measured
Product Analytics & Tracking: Partner with Product to define data goals for initiatives, and validate that data captured supports meaningful analysis
Analytics Engineering & Data Modelling: Build and oversee analytics models using dbt and Redshift, preferably following the Kimball approach, ensuring data is well-structured, performant, and fit for downstream analysis and BI
Stakeholder Engagement & Insight Translation: Work directly with senior leadership and shareholders to answer business questions, present insights, and recommend actions grounded in data
Team Leadership & Quality Control: Line-manage a data engineer, review Python and SQL work, set standards for analytics engineering, and establish sustainable team processes
Data Literacy & Visual Storytelling: Improve data literacy across the organisation and ensure insights are communicated clearly through well-designed dashboards and narratives
Benefits
Hybrid-working with 3/4 office days in our beautiful King's Cross, London office
