Graphic Deigner

Apply here https://tinyurl [dot] com/3tz4tkht

About Discovered Labs

At Discovered Labs we work with $10M - $50M ARR companies to help them get more leads, users and customers from Google, Bing and AI assistants such as ChatGPT, Claude and Perplexity.

We approach marketing the way engineers approach systems: data in, insights out, feedback loops everywhere. Every decision traces back to measurable outcomes. Every workflow is designed to eliminate manual bottlenecks and compound over time.

High-level overview of our approach:

Data-driven automation: We treat marketing programs like products. We instrument everything, automate the repetitive, and focus human effort on high-leverage problems.

First principles thinking: We don't copy what others do. We understand the underlying mechanics of how search and AI systems work, then build solutions from that foundation.

Full-stack ownership: SEO and AEO rarely work as isolated tasks. We work across the entire funnel and multiple surface areas to ensure we own the outcome and clients win.

The Agency OS

We're building the first agency OS: a system where the agency's work is the software, enabling clients to gain an unfair advantage.

As Karpathy puts it, Software 3.0 automates what humans can verify. Verifiability, not capability, decides which work can safely be handed over. So every eval we write expands the set of work we can trust an agent with, and the harness isn't overhead around the product, it's what makes the product possible. Dex Horthy covers the operational half: the agents that survive contact with customers are well-engineered software with human judgement placed deliberately, and disciplined loops beat vibes.

What that looks like here: expert orchestrators, not operators. One strategist supervising a fleet of agents running real client workflows at scale, with the system surfacing what genuinely needs a human decision and staying quiet about what doesn't. Feedback loops everywhere. Every correction an expert makes becomes an eval case, and the swarm is better the next cycle.

The Team

You'll join the Automations team at Discovered Labs. We build the agent swarm: a growing fleet of agents and workflows that do real client work end to end, and the engineering that makes them trustworthy enough to let loose on it.

Your mandate is both halves of that. Expand what the swarm can do, and prove that what it does is right. That means applying hardcore engineering to a famously slippery problem: making non-deterministic systems reliable, measurable and provable. Evals that fail a build. Traces that explain a decision. Guardrails that hold when a model doesn't. Agents that know what they don't know and say so.

You'll work alongside the Automations lead, and with our AI & Data team who own the platform and tooling underneath you. You won't be building orchestration from scratch or fighting for infrastructure. It's there, and it's good. Your job is to take it the last mile.

Every agent you make provable is an agent we can put in front of a client. That's the whole game, and the ceiling on how fast this company grows.

We're a deeply technical team building the SpaceX of the AEO & SEO space. You'll work alongside engineers who have built fraud engines powering Stripe, shipped AI code review at CodeRabbit, built at Amazon, developed self-driving car systems at Aurora, and conducted AI research at Stanford. We don't have layers of management. You'll work directly with founders who can go deep on architecture, code, and product.

This Role

You'll join the Automations team, and your job is to productionise what we've built.

We have live 24/7 agents, data pipelines and workflow infrastructure. What you’ll be doing is helping us get the stack running robustly, reliably and at scale.

That means evals that catch regressions before they ship, observability that explains why an agent did what it did, provenance that traces every claim back to its source, and interfaces that let a non-engineer SEO strategist run and review the work. You'll build the harnesses and eval suites that gate agent changes in CI, the lineage and step-trace tooling that makes agent reasoning inspectable, and the surfaces the team actually uses. Then you'll close the loop: instrument the output, feed the signal back, and make the agents measurably better every cycle.

You'll also extend what agents can reach. Today they work over APIs and our own data. Next they operate real websites along withsession handling, and navigating interfaces that were never designed for machines.

The hard problem is reliability and legibility. An agent that's right 80% of the time and can't tell you which 80% is worthless. An agent that's right 95% of the time, shows its working, and flags its own uncertainty is a product.

You report to the CTO and work alongside the Automations lead, with our AI & Data team owning the platform beneath you. You own your evals, your CI, and your monitoring.

What You'll Do

Agent eval harnesses. Golden suites, deterministic checks, and online scoring that gate every agent change in CI. A regression should fail a build, not a client report.

Agent observability. Step traces, token and cost accounting, run-level SLOs, and failure taxonomies. You'll know the difference between "the agent ran" and "the agent was right."

Data lineage and provenance. Every claim an agent makes should be traceable to its source. Which inputs, which tool calls, which reasoning steps produced this output.

End-to-end agents with human review. Agents that complete real work start to finish, with a curated review surface so an expert can approve, correct, or reject, and so that correction becomes training signal.

Interfaces for non-engineers. Dashboards and controls that let the SEO team run, inspect and trust agent work without asking an engineer.

Expanding what agents can do. Agents that open pull requests against real repositories, authenticate through OAuth, and operate real sites and CMSs through the browser. Every new capability is a new class of work the swarm can take on.

Closing the loop. Turn signals we already collect, such as AI perception and citation data, into concrete client value: strategy recommendations, prioritised actions, and measurable outcomes.

Algorithms and scoring models. Not everything should be a prompt. You'll build and tune the scoring systems behind what we recommend: internal linking and semantic relevance scoring, Reddit opportunity and thread scoring, content and citation quality. These are ranking and classification problems with real feedback data behind them, and where a model beats a prompt, you build the model.

Shared, composable modules. Reusable capability blocks that both agents and workflows compose, so an improvement lands everywhere at once instead of being reimplemented per agent.

Scaling across clients. Take a workflow that works for one client and make it run reliably for many, with per-client configuration, isolation, and failure that stays contained.

The Ideal Person for This Role

A builder who ships. You care about getting working systems into production, not endless planning or polish. You've built AI systems people actually rely on.

An operator, not just an architect. You don't just design systems, you run them. You find satisfaction in making things reliable, not just making them work once in a demo.

An owner. You take responsibility for outcomes, not just tasks. When an agent silently produces bad output, you catch it, fix it, and build the eval that stops it recurring.

Maniacal about detail. This is the one that matters most here. AI has made it trivially cheap to produce a large volume of plausible-looking work, and most of that work is slop. We are building the opposite: output that holds up when a client reads it line by line. If you'd rather ship one thing that is provably right than ten that are probably fine, this is your team. If you cannon volume and let the reviewer sort it out, it isn't.

Sceptical of your own output. You assume the model is wrong until measured. You've been burned by a demo that worked and a production run that didn't, and you build accordingly.

Humble and curious. You acknowledge what you don't know, ask good questions, and genuinely want to learn. You take feedback as a gift, not a threat.

A first-principles thinker. You understand why things work, not just how. You can go five levels deep on eval design, prompt architecture, and where to put the human in the loop.

Always improving. You're not satisfied with "good enough." You actively seek ways to get better at your craft and make systems better over time.

Requirements

5+ years in software engineering, with meaningful recent time on LLM-backed or ML-backed production systems, including 2+ owning a production system end to end.

Python, React, Typescript and strong systems fundamentals. You write production services, not notebooks.

LLM application engineering in production. Agents, tool use, structured outputs, retrieval, prompt architecture. You've shipped something real that used them and stayed up.

Evaluation systems. You've built eval suites for non-deterministic systems: golden datasets, regression gates, offline and online scoring. You've thought hard about what "correct" means when there are many correct answers.

Observability for AI systems. Tracing, run inspection, cost and token accounting. Langfuse, LangSmith, Braintrust, OpenTelemetry or equivalent.

Debugging non-determinism. You can diagnose why an agent failed on run 47 of 100 and turn that into a permanent check.

Pipeline orchestration. Airflow, Dagster, Temporal or similar. Retries, idempotency, partial failure, resumption.

Third-party API integration. Auth flows, rate limits, pagination, breaking changes. Not just calling endpoints, but handling the full operational reality.

Own your infrastructure. Containers, CI/CD, deployment, monitoring, credential management. No platform team to hand off to.

Product sense for expert users. You've built tooling that domain experts, not engineers, use daily. You know that an unexplained AI output is an unusable one.

Collaborative. You'll define contracts with the engineers who own the infra beneath you. You document decisions, write clear specs, and communicate tradeoffs in writing.

Preferred Qualifications

• Browser automation or authenticated web agents (Playwright, Puppeteer, computer-use models)
• Applied ML: ranking, scoring, classification, or recommendation systems in production
• Python, React, Typescript
• Terraform, Kubernetes
• Prior experience at a fast-moving startup

What's in It for You

• Fully remote position
• Work directly with the CTO on high-impact projects
• High ownership and autonomy. No micromanagement.
• First-hand exposure to cutting-edge AI and search technology
• Your work will directly impact well-known (10M+ ARR) companies' performance
• Join a fast-growing company at the intersection of AI and marketing

Our Hiring Process

1. Application
2. Technical Deep Dive
3. Reference Checks

Apply here https://tinyurl [dot] com/3tz4tkht

About the Role

Noéla is a premium luxury snack brand offering dark chocolate–covered dates crafted with high-quality nuts. We are hiring Sales Executives to expand our retail presence across cafés, gourmet stores, gifting boutiques, and corporate clients.

This is a commission-based field sales role in Delhi NCR with immediate joining.

Compensation & Earnings

Commission-based role (no fixed salary)

Typical monthly earnings: ₹5,000 – ₹35,000

Uncapped income potential (higher sales = higher earnings)

Monthly payouts + performance incentives

Key Responsibilities

Visit cafés, retail stores, and corporate clients in Delhi NCR

Onboard new stockists and generate orders

Drive repeat sales and maintain relationships

Ensure product visibility and placement in stores

Track competitor activity and market trends

Requirements

1–4 years of sales experience (FMCG/retail preferred)

Strong communication and persuasion skills

Self-driven and target-oriented

Comfortable with field sales

Products You’ll Sell

Premium dark chocolate dates (Almond & Pistachio variants) designed for cafés, gifting, and retail.

Location & Timeline

Location: Delhi NCR (Field Role)

Joining: Immediate

How to Apply

Apply via Platform

Position - HR 

Experience - 1-2 Years

Who are we

Based out of IIT Bombay, HaystackAnalytics is a HealthTech company creating clinical genomics products, which enable diagnostic labs and hospitals to offer accurate and personalized diagnostics. Supported by India's most respected science agencies (DST, BIRAC, DBT), we created and launched a portfolio of products to offer genomics in infectious diseases. Our genomics based diagnostic solution for Tuberculosis was recognized as one of top innovations supported by BIRAC in the past 10 years, and was launched by the Prime Minister of India in the BIRAC Showcase event in Delhi, 2022.

What we want you to do

• This role will comprise 70% TA & 30% of either functions (Admin/HR-Ops/Employee Engagement) depending upon the candidates skill set..
• Work with different department heads to understand the hiring requirement 
• Curate Job posts on Various platform 
• Recording keeping of resumes
• Maintain database of candidates
• Screen Resume as per requirement of the role. 
• Speaking to potential candidates & explaining them the JD
• Schedule Interviews via online meeting portals or face to face interviews.
• Ensure timely feedback from the interview panels. 
• Keep good rapport with the candidates.
• Closing the hiring process

What are we looking in you

• Graduate or PG degree in Human Resources Management or a relevant field
• Prior experience as an HR Recruiter
• Sound knowledge of all HR processes (e.g. recruitment, training, talent management ,etc.)
• Experience with resume databases and ATS
• Sound knowledge of the end to end recruitment process.
• Strong verbal as well as written communication skills. Good proficiency in English. 
• Exceptional time-management and organizational skills

Role Overview

This is a senior-level counselling and inside sales role involving high-quality lead conversion, advanced counselling, and mentoring of junior counsellors while consistently achieving higher revenue and performance targets.

Key Responsibilities

• Handle high-intent, high-value, and complex student leads
• Conduct advanced counselling, objection handling, and closing
• Achieve higher individual conversion and revenue targets
• Support, guide, and mentor junior counsellors
• Ensure strong follow-up discipline and CRM accuracy
• Contribute to achieving team-level sales and growth goals

Eligibility & Requirements

• Prior experience in inside sales, student counselling, or EdTech preferred
• Strong communication, persuasion, and closing skills
• Proven and consistent track record of target achievement
• Ability to guide, train, and support junior team members
• Process-driven and performance-focused mindset

Requirements

• 3.5+ years of experience in React JS and Redux
• Expert in React.j, ideally using TypeScript language extensions
• Good understanding of JavaScript Design Patterns
• Good experience writing front-end test cases
• HTML5, CSS3 and Responsive web design are mandatory
• Exposure to Scrum methodology and XP technical practices such as unit testing, pair programming, test-driven development, continuous integration or continuous delivery
• Self-motivated, fast learner, detail-oriented, team player and a sense of humour

About the Role

A DevOps Engineer in Snappymob configures, monitors, and manages the Cloud Management service. You should be able to identify the most optimal cloud-based solutions for our clients and maintain cloud infrastructures in accordance with the best practices and company security policies. 

Responsibilities

• Configures the AWS cloud management service and uses tools to monitor and manage their services carefully.
• Manages the full AWS Lifecycle, Provisioning, Automation, and Security.
• Works with customers, solution architects, and product teams to drive migrations.
• Assists in the execution of migration discovery workshops with large enterprise customers.
• Maintains Data Integrity, Data Recovery, and access control while you use the AWS application platform.

Requirements

• More than 2 years of working experience in DevOps and cloud management.
• Strong proficiency in AWS services and migrations.
• Ability to think critically, analyze and break down problems into manageable components.
• Ability to communicate and work well with others.

Advantages

• Experience with AWS cloud migrations.
• Possesses AWS certifications in solution architecting or DevOps.
• Experience with managing CI/CD and deployment of services to the cloud.
• Experience with containerization and orchestration solutions (eg: Docker and Kubernetes)

As one of Malaysia's top app development companies, Snappymob helps top brands in Malaysia and around the world turn their ideas into reality by creating impactful digital products. Our clients span from startups to multinationals across many industries including finance, media, healthcare, energy, and education.

By pairing awesome user experience design and solid software engineering, we strive to help our clients achieve success – while providing them with honest, no-nonsense advice.

Visit us at snappymob.com to find out more about what we do.

Looking for Experience PHP-Wordpress Developers.

Company Name: Reddensoft Infotech Pvt Ltd

Well versed with theme Creation from scratch and Plugin development in Wordpress.

Proficient with Woocommerce , Laravel will be an added advantage.

Experience in Payment Gateway have implementation. Working experience of Shopify .

Good knowledge on PHP, MYSQL, Javascript.

Wordpress plugin development
-Wordpress theme development
- PHP, MySQL, HTML, CSS, JavaScript & jQuery
- Object-oriented programming
- Git version control system
- Understanding of WordPress Coding Standards

Must have experience in WordPress (min. 2yrs) required.

· Candidates capable of seamlessly communicating in English with supervisor or clients.