Job Description & How to Apply Below
We are a well-funded Silicon Valley based Series A startup backed by top-tier VCs, pioneering a new model of acquisition-led growth. Instead of building software companies the traditional way—chasing customers with sales and marketing—we acquire entire businesses and reinvent them from the inside out.
Our founding team boasts a remarkable track record in AI and the startup ecosystem, with each member having previously steered AI startups to unicorn status ( Cresta.ai ).
Our approach is not SaaS:
We drive growth through acquisition and technology is our transformation engine. Each company we bring on board comes with complex workflows, legacy systems, and antiquated data structures. We turn that complexity into opportunity, designing platforms that unlock efficiency, scale, and profitability.
What's in it for you?
Working with cutting-edge AI technologies on real-world transformation problems
Collaborate with world-class talent across engineering, product, and operations
Making an impact from day one – your work directly shapes how we transform entire industries
Challenging environment with a plethora of growth opportunities
Competitive compensation and benefits
High ownership and visibility in a small, high-trust team
About the Role
Forward Deployed Engineers are our zero-to-one team. You embed directly with portfolio companies, understand their domain deeply, and solve the novel, high-stakes problems that turn legacy operations into AI-native businesses. You're here to break the back of hard problems, prove transformation hypotheses, and extract generalizable patterns that become platform across our entire portfolio.
Each acquisition is a new deployment. You'll inherit complex workflows, fragmented data, and skeptical operators. Your job is to ship working AI systems that deliver measurable business outcomes – then codify what worked into playbooks that accelerate every future acquisition
What you will do
Embed on-site with newly acquired companies to deeply understand their business, workflows, and pain points
Sit with end users—operators, managers, frontline staff—to understand adoption blockers and build trust
Pick genuinely high-stakes problems at the core of the business, not peripheral edge cases
Build highly scalable, data-driven platforms that connect to legacy IT systems
Build AI-powered applications leveraging cutting-edge LLMs—voice agents, workflow automation, intelligent assistants
Define the software architecture and code the product, applying ML as a major differentiator
Implement eval-driven development: every piece of LLM-written code isn't done until you have evals verifying efficacy
Trust-Building & Adoption
Build guardrails that protect against runtime failures while maintaining flexibility
Technical solutions are only half the battle – driving adoption through demonstrated reliability is the other half
Playbook Development & Product Extraction
Identify patterns across portfolio companies that can become reusable frameworks or platform products
Contribute to transformation playbooks that reduce time-to-value for each subsequent acquisition
Work with product teams to graduate successful solutions from bespoke implementations to scalable product
What we look for
BSc. or MSc. in Computer Science or comparable degree
At least 5 years of hands‑on coding experience as a full‑stack or backend‑heavy engineer
Exceptional problem‑solving abilities, effective communication, and teamwork skills
Comfort with ambiguity—you can walk into a newly acquired company with legacy systems and make order from chaos
Core Engineering Craft
Ship production systems, not just prototypes—you’ve taken things from zero to deployed
Comfortable across the stack, but depth in at least one area (backend, frontend, data)
Experience integrating with legacy systems, messy APIs, and undocumented data sources
AI/LLM Systems
Hands‑on experience building with LLMs—prompting, RAG, agents, tool use
Eval‑driven development mindset: you instinctively think "how do I measure if…
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