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we are a fast-growing global body care brand, built on a proprietary e-commerce platform, deep consumer insights, and a relentless focus on performance. Millions of women worldwide use our products, and we are on a mission to become one of the most influential body care brands globally.
We operate at extreme velocity, with high standards and an obsession with results. We believe in challenging conventional thinking, making data -driven decisions, and moving quickly from idea to execution.
We are looking for a Forward Deployed Engineer (FDE) to build and lead our company's AI transformation journey, serving as a rare opportunity for a highly strategic and deeply hands-on builder who thrives at the intersection of business, technology, and execution. In this role, you will have the ultimate playground to shape how our entire company operates, influence every major function, and create a lasting competitive advantage for a leading body care brand. Initially operating as an individual contributor partnering closely with the CEO and the Management Team. Over time, you will transition to build and lead a small, high-performing team as AI becomes an increasingly critical capability across our global e-commerce and retail operations.
To thrive in our high-pace environment, you must think like an owner, not a consultant, and be equally comfortable discussing macro business strategy with executives as well as writing code to solve a messy problem yourself. You are someone who embraces ambiguity, enjoys building from scratch, and is completely obsessed with execution. You possess the high emotional intelligence and empathy required to collaborate with non-technical stakeholders and build trust, yet you maintain the thick skin, resilience, and great sense of humor needed to handle direct communication and rapid structural pivots. Most importantly, you maintain an uncompromising commitment to quality and process improvement, ensuring that every automation or workflow you deploy actively drives our core business metrics forward without requiring hand-holding or constant reminders.
Your life at our company will look like
* Define and lead the company's AI strategy and execution roadmap.
* Identify the highest-impact opportunities for AI across all business functions.
* Prioritize initiatives based on measurable business value, speed of implementation, and scalability.
* Design, build, deploy, and continuously improve AI-powered workflows, tools, automations, and agents.
* Translate business challenges into practical AI solutions that improve performance, efficiency, and decision-making.
* Develop production-ready applications and workflows using modern AI technologies, APIs, agents, and automation frameworks.
* Drive adoption and behavioral change across teams.
* Partner directly with business leaders to identify opportunities and implement solutions.
* Evaluate emerging technologies, models, vendors, and platforms.
* Establish governance, standards, architecture, and best practices for AI development.
* Define and track success metrics for every AI initiative, ensuring measurable impact on growth, productivity, speed, efficiency, or cost.
You will thrive in this role if you have
* Strong technical foundation in Computer Science, Software Engineering, data Science, or a related field.
* 5+ years of experience building technology, data, AI, automation, or software solutions in high-performance environments.
* Proven experience identifying business opportunities and translating them into deployed AI products, agents, automations, or workflows that drive measurable business impact.
* Hands-on experience working with modern generative AI technologies, LLMs, agent frameworks, APIs, embeddings, automation platforms, and production deployments.
* Strong proficiency in Python, SQL, APIs, and data -driven application development.

Were hiring an AI Engineer to design and build the intelligence layer behind our autonomous offensive security platform.
Youll develop AI agents capable of performing vulnerability discovery and exploitation at the level of top human white-hat hackers - combining deep security expertise with advanced AI reasoning and decision-making.
This role, reporting directly to our Agent TL, offers the opportunity to define how AI transforms offensive cybersecurity.
Youll collaborate closely with AI researchers, software engineers, and security experts to translate penetration-testing workflows into intelligent, automated capabilities - systems that plan, execute, and adapt in real time.
If youre passionate about AI, thrive in fast-paced environments, and want to shape the future of autonomous cybersecurity - wed love to meet you.
Responsibilities
Design and implement autonomous AI agents for penetration testing and vulnerability exploitation.
Translate offensive security workflows into intelligent, multi-step reasoning systems.
Develop modules for exploit generation, payload delivery, and adaptive vulnerability scanning.
Collaborate with AI researchers to fine-tune and evaluate models that enhance reasoning, adaptability, and precision.
Build evaluation frameworks to measure exploit success, learning performance, and reliability.
Ship production-ready AI systems that improve the speed, depth, and scalability of security testing.
Establish best practices for safe and controlled deployment of AI agents in offensive environments.

We're looking for a DevOps Engineer to join our growing Infrastructure team.
You'll work alongside our DevOps team to design, scale, and optimize the cloud infrastructure powering our company's AI-driven platform. As our product and engineering organization continue to grow rapidly, you'll play a key role in improving reliability, automation, scalability, and developer productivity.
This is a highly hands-on role with significant ownership. You'll collaborate closely with R&D, AI, and Security teams to build reliable infrastructure, streamline development workflows, and help shape the future of our engineering platform.
Responsibilities
Design, build, and maintain scalable cloud infrastructure.
Develop and improve CI/CD pipelines and deployment processes.
Manage and optimize Kubernetes clusters and containerized environments.
Automate infrastructure using Infrastructure as Code (Terraform or similar).
Improve monitoring, observability, and system reliability.
Support production environments and troubleshoot infrastructure issues.
Collaborate closely with R&D, AI, and Security teams to improve developer experience.
Help define infrastructure best practices and drive operational excellence.

The Role & The Challenge
We are seeking a DevOps Engineer, at the mid or senior level, to join our infrastructure team, reporting directly to our DevOps Team Leader. Depending on experience, this role will either contribute to or help drive advanced infrastructure initiatives - from system design through production hardening - as we raise the bar for operational excellence across the company.
The immediate challenge: our company operates a high-volume, multi-account AWS environment. You will help solve complex delivery, scaling, and operational problems along the way. Scope and ownership will be calibrated to your experience level.
Responsibilities
Contribute to Cloud & Migration Strategy: Work alongside our DevOps Team Leader to help plan and execute our migration from ECS Fargate to Kubernetes (EKS) without downtime, while maintaining our existing cloud estate.
Advance Infrastructure as Code: Design and implement modern, modular IaC frameworks utilizing Terraform and OpenTofu to ensure consistent, multi-environment deployments.
Improve Enterprise CI/CD: Evolve our delivery pipelines (GitHub Actions, OIDC federation) at scale, reducing developer friction and elevating deployment safety across dozens of services.
Support Data-Intensive Infrastructure: Help maintain the performance, capacity, and resilience of our high-volume data layer (ClickHouse, ScyllaDB, DynamoDB, RDS, Redis) and event-driven messaging pipelines.
Strengthen Reliability & Observability: Help maintain organization-wide reliability standards using open, modern telemetry stacks (OpenTelemetry, Coralogix, Grafana), ensuring on-call operations are driven by signal, not noise.
Balance Growth & Governance: Participate in technical tradeoff decisions that balance velocity, least-privilege security, zero-trust access (Tailscale), and FinOps cost efficiency.

You are joining a small engineering team that is already shipping a live platform, and you will lead it. You own the architecture and set the technical direction as we scale from a working product to the system hospitals run their AI operations on: the connectors that read from the AI a hospital has deployed, the auditable record on top, and the monitoring the platform is growing into.
What you'll own
The architecture and hands-on build across the full stack, and the technical direction as the platform scales.
The connectors that read from hospital environments, the auditable AI record on top, and the roadmap into drift and performance monitoring.
The engineering foundations: code review, testing, CI/CD, and the security posture a hospital will interrogate.
Leading and growing the team, and owning the hiring bar.

A senior, hands-on engineer joining a small team that is already shipping a live platform. You own whole features end to end, from a rough problem to something running in production that a hospital relies on. You will not wait for a spec, and you help set the bar for how we build as we grow.
What you'll own
Whole feature verticals across frontend, backend, data, and cloud: the auditable AI record, the workflows around it, and the ingestion behind them.
The reliability of what you ship, including incidents on your own code.
Local architecture and tooling calls, made without escalating everything.
The engineering-quality bar a small team compounds on: review, testing, and the habits later hires inherit.

What You'll Do
- Build and harden AI Workers for real enterprise workflows - procurement, finance, HR, sales, risk, integration.
- Own the MCP connector framework - reusable tool servers that power every AI Worker.
- Design multi-step agentic flows with planning, reflection, retries, approvals, and clean failure modes.
- Ship evaluation suites that catch regressions before customers do.
- Instrument cost, latency, and reliability; drive them down relentlessly.
- Partner with Product and Solutions to ship features that survive contact with enterprise reality.

What You'll Do
- Build and evolve the Workflow Builder, Tables, and App Maker UIs - visual, drag-and-drop, real-time, collaborative.
- Design and ship the Gini AI Worker dashboards - run visualization, step traces, approvals, cost tracking.
- Own performance - sub-second interactions, optimistic updates, virtualized lists, edge-first rendering.
- Partner tightly with design + product on component systems, accessibility, and motion.
- Contribute to our design system - reusable, themable, keyboard-first.

What You'll Do
- Design and ship the ML backbone of Gini AI Workers - routing, tool selection, reasoning, memory, evaluation.
- Build evaluation and feedback loops - offline evals, online A/B, regression harnesses, human-in-the-loop labeling pipelines.
- Optimize cost and latency across the agent stack: prompt engineering, model routing (frontier ↔ small ↔ fine-tuned), caching, speculative decoding, distillation.
- Fine-tune and/or RAG-tune models for vertical enterprise tasks (invoice extraction, PO matching, ticket triage, forecasting).
- Own the ML infra - training pipelines, experiment tracking, model registry, deployment, monitoring, drift detection.
- Partner with backend + product to turn research into shipped features on a weekly cadence.

What You'll Do
- Own end-to-end solution design for enterprise deals - from first discovery call to signed SOW to production handoff.
- Lead technical discovery with CIOs, CTOs, and IT leads. Map their current stack (Priority / SAP / NetSuite / Salesforce / custom) and design the company blueprint.
- Architect multi-system integrations - ERP ↔ CRM ↔ e-commerce ↔ shipping ↔ AI Workers - using our company's MCP-native connector framework.
- Run live technical demos and POCs that prove value in days, not months.
- Partner with Sales on pricing, scoping, and risk assessment; be the "technical closer" on 6-7 figure deals.
- Partner with Product - bring real-world field signals back and influence the roadmap.
- Mentor the Professional Services team on architectural patterns and reusable process blueprints.

As an AI Algorithm Engineer at our company, youll design and implement advanced algorithmic workflows that power our data digestion pipelines and conversational AI agent experience. You will:
Architect and build workflows that turn raw, unstructured data (e.g., PDF documents and ultra high-resolution architectural drawings) into meaningful, structured context for downstream analysis.
Combine techniques from classical NLP, computer vision, unsupervised learning, and graph theory to build robust end-to-end pipelines - not just standard LLM API calls, but intelligent decomposition, structuring, and context engineering.
Develop AI agent workflows that let customers explore, query, and reason about their data naturally and reliably.
Build strong evaluation infrastructure to benchmark and continuously improve both classical algorithmic components and LLM-based workflows.
Work primarily in Python, and collaborate across systems and services in TypeScript when needed.
Move fast from prototype to production, while maintaining correctness, scalability, and measurable quality.

Required Full Stack Developer
Full-time
Company Description:
A dynamic technology firm dedicated to building exceptional products using modern technologies for the world's most admired companies. We pride ourselves on innovation, collaboration, and delivering excellence in every project.
Job Description:
Design and develop web applications from concept to deployment.
Collaborate with UX/UI designers and backend developers to create a cohesive product.
Manage databases and optimize server-side logic for performance.
Implement and maintain APIs for frontend-backend integration.
Troubleshoot and debug issues across the application stack.