Why Cast AI?

Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, Cast AI continuously optimizes performance, reliability, and efficiency in production.
The old way doesn't work. As Kubernetes and AI environments grow, manual decisions don’t. Cast AI replaces tickets, alerts, and manual tuning with continuous automation that adapts infrastructure as conditions change. Efficiency and cost savings follow naturally from that automation.
Over 2,100 companies already rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS.

Global team, diverse perspectives

We're headquartered in Miami, but our impact is international. We take a global and intentional approach to diversity. Today, Cast AI operates across 34 countries spanning Europe, North America, Latin America, and APAC, bringing a wide range of perspectives into how we build and lead.

Unicorn momentum

In January 2026, we achieved unicorn status with a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group (a $50+ billion Korean conglomerate). Our valuation now exceeds $1 billion, and we're just getting started.

Join us as we build the future of autonomous infrastructure.

About the role

Throughput. Latency. KV cache utilization.

Move those three numbers in the right direction, and two things happen: customers get faster, cheaper inference, and our margins improve. That's the entire thesis of this role. Every kernel you tune, every quantization scheme you ship, every scheduler tweak you land shows up directly in a customer's p99 and on our P&L.
This is a high-impact seat. It is also a high-autonomy seat as you'll be given the room to lead the technical direction of inference optimization at Kimchi, not execute someone else's roadmap.

The problem: running LLMs in production is a moving target. The "right" model and serving configuration for a workload depend on traffic shape, sequence-length distribution, batch dynamics, GPU SKU, memory bandwidth, quantization tolerance, and a dozen other variables that shift week to week. Most teams pick a model once, over-provision GPUs, and absorb the cost. Kimchi is the system that makes that decision automatically - continuously matching workloads to the most cost-efficient, best-performing LLM and serving configuration on a customer's infrastructure. We're building the optimization layer between the model and the hardware, and we need engineers who understand both sides deeply.

Stack

Python; vLLM; SGLang; TensorRT-LLM; PyTorch; CUDA-adjacent tooling; Kubernetes; gRP; ClickHouse; PostgreSQL; GCP Pub/Sub; AWS / GCP / Azure; GitLab CI; ArgoCD; Prometheus; Grafana; Loki; Tempo.

Requirements:

• 5+ years building real ML systems, with a portfolio that shows depth in inference or training infrastructure (not just model training notebooks).
• Strong Python - production services, not scripts.
• Hands-on experience with at least one of vLLM, SGLang, or TensorRT-LLM, and a working mental model of why an inference engine performs the way it does on a given GPU.
• Fluency with quantization tradeoffs - you've measured quality regressions, not just compression ratios.
• Comfort with distributed systems: collective communication, sharding strategies, and the practical failure modes of multi-GPU and multi-node setups.
• A bias toward measurement. You instrument before you optimize, and you can tell the difference between a real win and a benchmark artifact.
• Self-direction. This role comes with a wide mandate; you should be excited by that, not unsettled by it.

Responsibilities:

• Push throughput. Continuous batching, speculative decoding, chunked prefill, kernel-level tuning across vLLM, SGLang, and TensorRT-LLM. Find the ceiling on each GPU SKU, then raise it.
• Cut latency. Attack TTFT and TPOT separately. Profile, identify the actual bottleneck (compute, memory bandwidth, scheduling, networking), and fix it - not the bottleneck you assumed.
• Get more out of the KV cache. Paged attention, prefix caching, eviction policies, cache reuse across requests, quantized KV. This is where a lot of the unrealized throughput lives, and it's an area you'll own.
• Quantize without regressing quality. INT8, INT4, FP8 across weights, activations, and KV. Empirical work: measure quality on real workloads, not just perplexity benchmarks.
• Shrink cold starts and memory footprint. Faster init, smarter weight loading, tighter memory accounting - the difference between a model that scales and one that doesn't.
• Scale across nodes. Distributed inference topologies, network-aware placement, checkpointing strategies that don't bottleneck on storage or interconnect.
• Set the technical direction. Decide what we benchmark, what we adopt, and what we build ourselves. Bring the team along with strong writeups and reproducible experiments.

What’s in it for you?

• Competitive salary (depending on the level of experience).
• Enjoy a flexible, remote-first global environment.
• Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology
• Equity options.
• Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks.
• Spend 10% of your work time on personal projects or self-improvement. 
• Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills.
• Annual hackathon to spark new ideas and strengthen team bonds.
• Team-building budget and company events to connect with your colleagues.
• Equipment budget to ensure you have everything you need.
• Extra days off to help maintain a healthy work-life balance.

Hiring process

• Screening call with Recruiter
• Hiring Manager interview
• Technical interview (system design)
• Live coding
• Culture Check interview with an executive

As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr.
Please note that Cast AI does not provide any form of visa sponsorship/work permit.

#LI-Remote

GTM Engineer at Unframe

Location: Remote (Global)

About Unframe

Unframe is an AI-first startup helping the world’s largest enterprises bring LLM-powered applications to life in days - not months. We combine the speed of a product company with the flexibility of a consultancy, helping customers move from idea to deployed AI systems faster than anyone else in the market.

Backed by Bessemer, Craft, and TLV Partners with $50M in Series A funding, we’re building a fast-growing, revenue-generating company working with Fortune 500 customers globally

About the role:

We’re hiring a GTM Engineer to build the systems that power our GTM motion and enterprise sales execution.

You will design and implement the automation, tooling, and data infrastructure that turns GTM strategy into repeatable pipeline. You’ll work directly with Sales Leadership, Enablement, Marketing, and Solutions to remove friction, increase selling time, and scale outbound in a thoughtful way.

If you enjoy creating systems that make sales teams materially more effective, this role is for you!

What you’ll do:

• Build scalable outbound infrastructure, including account selection, sequencing, enrichment, and routing, aligned to ICP and vertical strategy
• Design and maintain automations and integrations across Salesforce and the GTM stack that eliminate manual work for AEs and SDRs
• Create and manage GTM Agents built in support of seller productivity and GTM execution
• Partner with Sales Leadership, Enablement, and Marketing to ensure systems reinforce how we sell
• Evaluate and implement new tools and light scripting (APIs, automation platforms) with scale and maintainability in mind

What we are looking for:

• 3–6 years in Sales Ops, RevOps, Growth Ops, or a GTM Engineering-style role
• Experience supporting enterprise or complex B2B sales
• Proven track record building outbound or pipeline automation
• Strong CRM fluency (Salesforce preferred)
• Experience with sequencing and enrichment platforms
• Comfortable working with structured data (SQL or similar is a plus)

Why join us?

• Real ownership from day one. Drive decisions, shape ideas and make them work.
• Your fastest learning years. Build alongside founders and VPs in a space that moves weekly.
• You'll have the opportunity to write and build what comes next.

Ready to Build the Future?

If this opportunity excites you, apply now!

The Team:

You’ll join the Value Engineering team, a highly technical, strategic, customer-facing group that sits at the intersection of pre-sales, analytics, and transformation consulting. Value Engineers at Celonis are hands-on practitioners. They combine strong technical capability with consulting and stakeholder skills to guide customers through the full value journey — from first demo to long-term adoption and expansion.

The Role:

As an Applied AI Engineer (Pre-Sales) you are pushing the envelope in solving business-critical problems for our customers. You will be working with our most strategic customers, understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

The work you’ll do:

• AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
• Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
• Ensure Successful Project Outcome: Applied AI Engineers stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Applied AI Engineers specialize in domains (e.g. supply chain) and industries

The qualifications you need:

•  3+ years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
• Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
• Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
• Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• Bachelor’s Degree required, Masters Degree in computer science, physics, engineering, mathematics or related fields, or equivalent work experience preferred.
• Hybrid working environment - 3 days per week at our central Milan offices.  

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex)

RDQ326R15

The Incident Response team's mission is to respond to security threats, incidents and investigations to protect our customers, employees and enterprise data in a fast, efficient and standardised manner. We're a tight-knit team of security incident responders and incident handlers doing "Security for Databricks on Databricks", using our own platform to create near-real-time log analytics, alerting and forensics.

You will be an individual contributor on the security Incident Response (IR) team at Databricks, reporting to the regional IR manager. You will be responsible for conducting security analysis and forensics, responding to high-priority alerts and contributing to automations and agentic capabilities. You will be a security multiplier and help the team scale security incident response at Databricks.

The impact you will have:

• You will respond to incidents as part of a distributed 24x7 operations and on-call schedule.
• You will triage and respond to security events and alerts, ensuring quick and effective containment.
• You will contribute to security investigations, conducting analysis and forensics across a range of data sources to determine the timeline and impact of security events.
• You will build automations, including leveraging AI and agentic platforms, to deliver autonomous capabilities, expedite your work and scale the impact of the team.
• You will communicate technical decisions through design docs and tech talks, and mentor junior security responders via security guidance, design reviews and code reviews.

What we look for:

• Bachelor's Degree AND 4+ years experience in Incident Response work OR Master's Degree AND 2+ years experience.
• Strong cloud security background in at least 1 of AWS, GCP or Azure, and working knowledge of the others.
• Knowledge of AI/LLM and agentic capabilities, including effective prompting and use of MCP, agents and agent skills. Prefer experience with building and operating agentic systems in a security setting.
• Broad security subject matter expertise.
• Expertise in few core IR skills (DFIR , Reverse Engineering, Traditional Network Security, Storage and access security, Sandboxing, Compute security, etc.).
• Experience with Enterprise Security and SaaS applications.
• Working knowledge of a SIEM and SOAR.
• Experience building Incident Response Tooling and scripting language skills.

Strategic Account Executive 

Location: Italy, Remote 

About Unframe

Unframe is an AI-first startup helping the world’s largest enterprises bring LLM-powered applications to life in days - not months. We combine the speed of a product company with the flexibility of a consultancy, helping customers move from idea to deployed AI systems faster than anyone else in the market.

Backed by Bessemer, Craft, and TLV Partners with $50M in Series A funding, we’re building a fast-growing, revenue-generating company working with Fortune 500 customers globally

About the role:

We’re looking for Strategic AEs to join our team and help drive our go-to-market motion. You’ll play a pivotal role in landing our first major customers, shaping our sales playbook, and partnering directly with the VP of Sales and founder to build a high-performance revenue engine.

What you’ll do:

Drive Enterprise Transformation

Lead complex, multi-stakeholder sales cycles into highly regulated industries (FinServ, Healthcare, Manufacturing, Retail) where our on-premises capabilities provide a competitive advantage.

Own the Full Sales Cycle

Build pipeline from zero in an early-stage environment—identify and win strategic enterprise accounts with no hand-raisers or established playbook.

Solution Architecture

Translate complex AI/ML capabilities into compelling business outcomes for C-suite stakeholders, positioning Unframe for companies seeking to “buy vs. build” AI capabilities.

Account Expansion

Architect multi-year expansion strategies and build deep relationships across IT, product, and innovation teams.

Go-to-Market Partnership

Collaborate directly with the VP of Sales and founders to refine the enterprise strategy and influence the product roadmap

What we are looking for:

8+ years enterprise software sales with consistent quota over-achievement at Fortune 500 companies

Proven track record closing $1M+ ACV deals in early-stage environments

Experience selling complex technical solutions to CIO organizations

Background in AI/ML platforms, digital transformation, enterprise data platforms, or management consulting

Entrepreneurial mindset, you thrive in ambiguity, own outcomes, and build from scratch

Success in highly regulated industries with complex compliance requirements

Nice-to-Have Skills:

Regulated industry experience, early-stage success

Why Join Us

• Compensation is uncapped with aggressive accelerators. At $1M+ ACV deal sizes, this structure rewards over-performance on meaningful deals.
• Our VP of Sales joined Unframe for three reasons: a founder with a proven exit, tier-one investors, and a product that's genuinely different and defensible. The GTM approach backs that up. Buyers get a free POC, tailored to their actual use case, delivered in days. No data sharing, no upfront cost, no six-month consulting engagement before anyone sees value.
• You'll work directly with the VP of Sales and founders, shape GTM strategy, close the deals that define our market position, and hold equity in a company with real institutional backing and momentum.
• We hire with intention. If you thrive in a performance culture with real backing behind you, you will win here.

Ready to Build the Future?

If this opportunity excites you, apply now!

THE MISSION

We are looking for a Growth Marketing Specialist to join our Growth Marketing team and take ownership of the B2B self-service pipeline, the engine that turns inbound merchant requests into live partnerships across Italy, Spain, France, and Portugal.

You will think strategically, challenge proposals critically, and drive performance improvements through data, experimentation, and a deep understanding of digital advertising platforms. You will guide an external media agency on campaign operations and coordinate with the internal creative team on ad concepts, while also being hands-on: leveraging AI to prototype assets, building landing pages, and running experiments with the support of advanced LLM tools.

KEY RESPONSIBILITIES

• Own the performance of B2B paid campaigns across Google Ads and Meta Ads, guiding an external agency to ensure the best strategic and tactical decisions are made;
• Manage and evolve HubSpot workflows powering the self-service pipeline: lead qualification, automated communications, deal progression, and merchant nurturing;
• Collaborate with the Product team on a new B2B onboarding portal (in-store and online), ensuring CRM integration and communication triggers are correctly configured;
• Design, execute, and analyze A/B tests across the merchant funnel: landing pages, email sequences, onboarding touchpoints;
• Analyze campaign and funnel data to extract actionable insights and connect advertising performance to actual business impact;
• Monitor and optimize cost per Qualified Deal across all active markets.

WHAT WE ARE LOOKING FOR

Experience & Background

• 3-4 years of experience in growth marketing, performance marketing, or demand generation, ideally B2B;
• Hands-on experience managing paid campaigns on Google Ads and Meta Ads with a total annual budget of at least EUR 500K;
• Experience with a CRM platform (HubSpot strongly preferred): managing workflows, automations, and deal pipelines;
• Versatility across paid media, CRM, and analytics, whether built in agency, consulting, or in-house environments.

Technical Skills

• Google Ads & Meta Ads: conversion events, pixel/CAPI setup, optimization signals, attribution models;
• CRM (HubSpot preferred): workflow building, deal pipeline management, custom properties, attribution improvement;
• Analytics: confidence with at least one platform (Amplitude, Google Analytics, HubSpot Analytics);
• AI/LLM Tools: proven experience using advanced LLM tools (e.g., Claude Code, Codex) to accelerate analysis and experimentation;
• A/B Testing: solid understanding of control groups, test design, and statistical significance.

Mindset

• Analytical, data-driven, and comfortable digging into data to find the "why" behind a metric shift;
• Critical thinker who investigates when something doesn't add up;
• Proactive and solution-oriented;
• Strong communicator in both Italian and English.

Nice to Have

• Experience in fintech, payments, or e-commerce;
• Familiarity with SQL (JOINs, aggregations, filtering).

Recruitment Process:

1. A conversation with our Talent Acquisition team;
2. A first interview with the Hiring Manager to deep dive into your experience and role expectations;
3. A skills-based exercise and debriefing session involving key stakeholders;
4. A final chat with Simone (our CEO) where he will share and assess the Scalapay Values.