Lead Software Engineer – Elvoro Ltd Engagement: Full-time (40h/week) Location: Remote Compensation: $3,000.00 / month ($1.5K base + $1.5K performance, ≥80%) Trial Period: 30-day paid probation ($2000.00) Overview We are seeking a creative and self-directed content associate to handle all non-technical operations of the company, from social media content production to day-to-day administrative tasks. The founder defines weekly business outcomes and you execute independently. About the Company Elvoro Ltd is an innovative AI marketing technology company. We are an early-stage, founder-led company focused on selling and improving an MVP centered on AI-driven social media management and content generation. The team is small and engineering-driven, with an emphasis on speed, clarity, and practical execution. Responsibilities & Deliverables - Build, optimize, and maintain large-scale Python pipelines for AI-driven content generation and scheduled posting across all major social media platforms (Instagram, TikTok, YouTube, Facebook, X, Threads, Snapchat, and more) - Integrate and manage numerous third-party APIs — including AI services for social media, text, image, video, voice, and sound — and evaluate output quality for social media performance - Build, manage and optimize AI agents for social media workflows. Design scalable, reusable automation pipelines that serve multiple clients and creative workflows, with a path toward self-service capabilities and AI agent integration - Own the GitHub repository end-to-end: clean code, proper branching, documented commits, and written summaries for every completed task - Automate client reporting (analytics across all published content and platforms) and handle all other technical tasks as directed by the founder - Complete tasks fully independently, be proactive and solution-orientated on your own, take ownership and technical responsibility Qualifications - 5+ years of professional Python development experience with a focus on automation and pipeline engineering - Tech stack: Python (advanced), REST APIs / HTTP clients, GitHub / Git, Google Cloud Platform (GCS, Cloud Functions, etc.), JSON/CSV data handling, Bash / Linux CLI, SQL / database fundamentals, task scheduling (cron, Celery, or similar), virtual environments and dependency management - Proven track record building and scaling complex automation workflows integrating multiple APIs in production environments - Comfortable managing a codebase independently: GitHub workflows, technical decision-making, and clean documentation - Experience with AI/ML APIs (LLMs, image generation, video generation, TTS) and social media platform APIs, with an eye for evaluating creative output quality - Independent, solution-oriented, and proactive with strong communication skills. Fast-paced early-stage environment. - Fluent in English (written) Benefits Compensation of $3,000/month for a full-time remote engagement. All tools and resources required for the job are provided and paid for by the company, including GitHub seats, API access, and AI subscriptions. Direct one-on-one collaboration with the founder, with full technical ownership and meaningful influence over the product. Opportunity to work at the cutting edge of AI-powered automation and grow into a senior technical role as the company scales.

Job Description: AI/ML Engineer (SD1/SD2) Location: Remote / Bangalore Type: Full-time Team: AI/ML Engineering About Disseqt AI Disseqt AI helps enterprises build safe, reliable, and compliant AI systems. We develop cutting-edge evaluation, safety, and monitoring capabilities that ensure AI applications behave consistently, securely, and responsibly in production environments. We are building the next-generation AI safety stack — combining machine learning, smart evaluation systems, and scalable engineering. If you love working at the intersection of ML models, systems engineering, and real-world AI reliability, this role is for you. Role Overview We’re looking for an AI/ML Engineer (SD1/SD2) who can design, train, and deploy machine learning models and build production-quality ML services. You’ll work across model development, evaluation pipelines, and backend integration to support scalable AI systems used by enterprise customers. This role sits at the heart of our ML platform — combining applied machine learning, NLP, model optimization, and service engineering. What You Will Do Machine Learning & NLP - Build and optimize ML models for text classification, semantic scoring, and evaluation tasks - Develop hybrid ML pipelines combining classical ML, embeddings, and rule-based techniques - Work with transformers, embeddings, and lightweight inference-optimized architectures - Benchmark multiple models for accuracy, latency, and reliability Production ML Engineering - Build containerized ML services (Python/FastAPI) for high-performance inference - Optimize models for CPU-only execution and on-prem deployment - Implement scalable inference pipelines and internal APIs for model serving - Ensure reliability, uptime, and versioning of ML services Evaluation & Observability - Develop automated evaluation pipelines for model performance and quality - Instrument ML services with tracing, logging, and metrics - Work closely with backend engineers to integrate ML outputs into platform workflows Safety & Quality Systems - Train and refine models for text safety, classification, detection, and quality scoring - Build logic to combine statistical, ML, and heuristic signals - Contribute to robust testing frameworks and red-teaming workflows Engineering Collaboration - Work with platform, backend, and infra teams to deploy ML workloads - Write clean, maintainable code and contribute to internal tooling - Participate in code reviews, architecture discussions, and sprint planning What We’re Looking For Required Skills - Strong proficiency in Python for ML development - Experience with ML model training and classical ML (SVM, Logistic Regression, XGBoost, etc.) - Experience with NLP libraries (Transformers, spaCy, sentence-transformers) - Familiarity with model evaluation, metrics, and benchmarking - Ability to build APIs/services for ML inference (FastAPI/Flask) - Understanding of containerized deployment (Docker) - Comfortable working with data preprocessing, dataset creation, and experimentation Good To Have - Experience optimizing models for CPU or resource-constrained environments - Knowledge of embeddings, similarity scoring, and semantic search - Exposure to ML observability, logging, or tracing systems - Experience with rule-based + ML hybrid systems - Hands-on experience with Redis, PostgreSQL - Basic understanding of Golang is a plus - Exposure to agentic/LLM systems, evaluation frameworks, or safety research Who Will Thrive in This Role - Engineers who enjoy owning ML problems end-to-end — model → API → deployment - Those who love practical ML, not just research - Builders who like shipping to production, not just prototyping - People who enjoy working in fast-paced, deeply technical teams - Those passionate about the reliability and governability of AI systems Why Join Us - Work on high-impact ML problems in a rapidly evolving domain - Build real-world AI systems trusted by enterprise customers - 100% ownership of projects with end-to-end visibility - Solve technically challenging ML problems with a top-tier engineering team - Competitive salary + equity

Founding GTM Engineer Location New York City or U.S. Employment Type Full-time Location Type On-site, Hybrid, or Remote Department Revenue & GTM Engineering Compensation • Competitive base salary • Performance-based commission • Equity About Evergrid Evergrid builds the infrastructure that powers advanced artificial intelligence at scale, with the Most Advanced Neocloud. We design and operate critical GPU and power infrastructure for frontier AI workloads — environments where performance, reliability, and execution are non-negotiable. Our customers are building systems at the edge of what’s possible, and they depend on infrastructure that scales quickly and works under sustained pressure. We care deeply about outcomes, ownership, and building durable systems and long-term partnerships. The Role As a Founding GTM Engineer, you will help design and implement go-to-market systems to win mindshare and grow our top-of-funnel. This role is focused on building simple, high-impact workflows that scale. You’ll be expected to generate high-impact ideas and quickly implement working GTM motions. We value speed, clarity, and leverage — lightweight systems that work today and can scale tomorrow without adding unnecessary complexity. If you enjoy moving fast, testing ideas in the real world, and turning small systems into meaningful impact, this role is for you. What You’ll Do Build modern GTM Systems - Design and build on Evergrid’s go-to-market and sales engineering workflows - Build simple automations across HubSpot, Make.com, Clay, and internal tools - Prototype new outbound, inbound, and qualification workflows - Replace manual sales work with creative automation and AI-driven processes - Test GTM ideas quickly and scale what works AI-Driven Sales Acceleration - Use modern AI models (ChatGPT, Grok, Gemini, and others) as building blocks - Create workflows for prospect research, personalization, account mapping, and follow-up - Design AI-assisted systems for founder-led sales and enterprise deal support - Explore agent-style workflows to reduce time-to-meeting and time-to-close Sales Engineering & Deal Support - Support live deals with technical context and clear customer-facing explanations - Translate GPU and cloud infrastructure concepts into simple, compelling narratives - Assist in pilots, proofs of concept, and custom enterprise deal flows - Act as a bridge between sales, founders, and infrastructure teams Learning, Iteration & Optimization - Identify friction in the sales process and design systems to remove it - Track what’s working and iterate based on real results - Build feedback loops between GTM data and execution - Document systems so successful experiments become repeatable What We’re Looking For - Strong systems thinker with a bias toward experimentation and execution. - Comfort operating in ambiguity and learning quickly - Experience with automation platforms (HubSpot, Make.com, Zapier, APIs, or similar) - Heavy user of AI tools (ChatGPT, Grok, Gemini) to accelerate ideation and execution - Technical curiosity and ability to learn complex products - Clear written and verbal communication - High ownership mindset Nice to Have - Exposure to enterprise or technical sales environments - Experience with enterprise & AI-Native cloud sales, Neocloud, GPU Cluster buyers - Background in startups or fast-moving environments - Basic scripting or API experience

Role Overview We are seeking a technically deep, hands-on Solutions Engineer with strong enterprise contact center and customer experience expertise, combined with a startup and builder mindset, to lead the design, prototyping, and hardening of AI-driven solutions for large enterprise prospects. This is not a traditional demo-focused Sales Engineer role. This role operates as an applied AI systems architect and builder in a pre-sales environment. You will translate enterprise workflows into structured, demo-ready AI architectures and personally build working prototypes that validate feasibility under real-world constraints. You must be comfortable owning technical design end-to-end, operating with high autonomy, executing under executive visibility, and driving technical outcomes without relying heavily on downstream teams. What You’ll Do Applied AI Solution Architecture - Design and prototype enterprise-grade, AI-driven customer experience demo solutions, translating business logic into structured reasoning frameworks. - Architect robust retrieval, orchestration, and validation systems, building scalable prototypes that tolerate real-world data variability. - Own the transition from early-stage prototype to hardened proof of concept. Enterprise CX & Contact Center Expertise - Apply deep knowledge of enterprise contact center ecosystems, including CCaaS, CRM, ticketing systems, digital messaging, routing logic, escalation flows, QA models, and reporting structures. - Work directly with CX, Operations, Digital, IT, and Architecture stakeholders to understand real-world workflows and constraints. - Convert operational processes into AI-enabled workflows that align with containment, handle time, SLA, QA, escalation rate, and customer satisfaction metrics. - Identify integration patterns across enterprise systems and design practical implementation approaches. Enterprise Discovery & Technical Navigation - Lead rigorous technical discovery sessions across multi-layered enterprise organizations. - Extract clear architecture and data requirements from ambiguous or politically complex environments. - Identify logic gaps, data fragmentation, compliance constraints, and integration risks early in the engagement. - Document architecture, assumptions, and technical success criteria clearly. Strategic Pre-Sales Partnership - Partner closely with Account Executives to shape technical strategy within enterprise accounts. - Scope engagements realistically, balancing ambition with execution feasibility. - Articulate architectural tradeoffs clearly to both executive and technical audiences. - Influence enterprise stakeholders on integration patterns and AI implementation approaches. - Contribute to scalable solution design that supports long-term account expansion. Execution Expectations - Operate independently in fast-moving, ambiguous environments. - Rapidly build working prototypes under tight timelines. - Take full ownership of technical outcomes rather than relying on downstream teams to validate feasibility. - Design with production realities in mind, not just happy-path demonstrations. - Maintain a consistently high conceptual and technical bar in AI-driven systems. - Deliver artifacts that withstand executive and architectural scrutiny. Required Experience Enterprise CX & Contact Center Background - 5+ years of experience in enterprise customer experience, contact center, or customer support technology environments. - Strong familiarity with CCaaS platforms, CRM systems, routing frameworks, digital messaging channels, escalation models, and reporting metrics. - Experience modeling solutions against operational KPIs including containment, AHT, SLA, escalation rate, QA score, and CSAT. - Demonstrated experience working with enterprise stakeholders across Operations, IT, Digital, and Architecture teams. Enterprise Stakeholder Navigation - Proven ability to lead technical discovery in complex, multi-stakeholder enterprise accounts. - Experience extracting structured requirements from ambiguity. - Track record of influencing architectural decisions and technical direction within enterprise environments. - Comfortable pushing back constructively on scope, feasibility, and risk. Applied AI & Systems Engineering - Hands-on experience building AI-driven applications using large language models or similar technologies. - Experience structuring reasoning flows, orchestration logic, and decision frameworks. - Practical experience designing retrieval strategies across structured and unstructured knowledge sources. - Strong Python proficiency including API client development, data normalization, error handling, and test harness construction. - Experience building lightweight internal tools or utilities to accelerate solution development. - Experience debugging multi-system interactions across AI behavior, logic layers, and integration layers. - Familiarity with version control and structured testing practices. Cloud & Integration Foundations - Working knowledge of cloud architecture patterns, including event-driven systems, middleware, and scalable API design. - Experience integrating enterprise SaaS platforms using REST APIs and webhooks. - Understanding of data modeling, schema design, and system scalability considerations. - Familiarity with at least one major cloud platform. Startup & Builder Mindset - Experience operating in high-growth startups or similarly fast-paced environments. - Demonstrated history of building complex systems independently. - Comfortable operating without rigid structure or fully defined requirements. - High ownership mentality with minimal dependency on external resources. - Bias toward shipping validated, working systems over producing theoretical designs. What Sets You Apart - You move from whiteboard architecture to working prototype in days, not weeks. - You design systems that withstand real-world enterprise constraints. - You think in workflows, integration boundaries, and measurable outcomes. - You are equally comfortable discussing routing logic with contact center leaders and debugging APIs or AI behavior. - You hold a high technical standard and proactively design guardrails and validation into your builds. Success in This Role Looks Like - Independently leading technical discovery that results in clearly documented architecture and defined success criteria. - Delivering production-grade proofs of concept that withstand executive and architectural scrutiny. - Identifying integration, data, and logic risks before late-stage deal pressure. - Shipping working technical artifacts that reduce reliance on downstream teams. - Translating AI system behavior into measurable operational and financial impact. This Role Will Not Be a Fit If - You prefer highly structured requirements before beginning work. - You are uncomfortable being the primary technical owner in high-visibility enterprise deals. - You rely heavily on product or engineering teams to validate feasibility before building. - You view pre-sales primarily as presentation-driven rather than execution-driven. Who This Role Is For - This role is ideal for a technically strong builder with deep enterprise CX experience who wants to operate at the intersection of AI engineering and enterprise solution architecture. - You are comfortable navigating executive conversations, designing scalable integration patterns, and personally building the systems that validate your architectural thinking. - If you are seeking a traditional demo-focused Sales Engineer role or one centered primarily on slideware and handoffs, this role will not be the right fit. Benefits and Perks: - Market-competitive total compensation package - 100% company paid family medical and 100% individual dental and vision insurance coverage - Flexible, unlimited vacation policy - Stock options - Strong company culture Quiq is an equal opportunity employer. We are a welcoming place for everyone, and we do our best to make sure people feel supported and connected at work. Applicants need to have the authority to work in the US. As we are at an early stage, immigration sponsorship is not available.