Regional Sales Head

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

Mandatory (Experience 1): Must have 6+ years of relevant experience in customer-facing Customer Success / Account Management / Implementation roles.

Mandatory (Experience 2): Must have 3+ years of hands-on experience supporting enterprise customers in North America and/or Europe

Mandatory (Experience 3): Must have owned end-to-end enterprise customer implementations, including discovery, onboarding, integrations, go-live, and stabilization.

Mandatory (Experience 4): Must have experience working with CXO / VP / Director-level stakeholders as primary points of contact (POCs) for enterprise accounts.

Mandatory (Experience 5): Must have managed enterprise accounts with ACV / ARR of at least USD 40K+, and owned commercial outcomes such as renewals, expansions, upsells, and retention (NRR).

Mandatory (Experience 6): Must have worked in B2B SaaS companies with complex technical products

Mandatory (Experience 7): Must have a conceptual understanding of SaaS architecture and APIs, with the ability to troubleshoot workflows and coordinate closely with engineering and product teams (hands-on coding not required).

Mandatory (Compensation): Candidate's Current CTC should not be less than 27 LPA.

We are seeking an experienced Developer with a strong background in C++, CUDA programming, and Linux to guide our development team in building cutting-edge solutions for device integration and high-performance computing tasks. This is a hands-on leadership position that combines technical expertise with team management skills to deliver high-quality software products.

No of position – 2

Duration – 1 year contractual position (candidate will be on Hiring Panda Payroll)

Experience Range – 4 to 5 years

Notice Period – Immediate, candidate should join within 7 days

Location – Kandivali, Mumbai (Only local candidates of Mumbai is acceptable)

Work Mode- Work from Office

Primary responsibilities:

Software Development:

• Develop and maintain high-performance applications using C++ and CUDA.

• Design and implement parallel algorithms for GPUs to accelerate computational

workloads.

Performance Optimization:

• Optimize CUDA kernels for performance, scalability, and memory efficiency.

• Analyze performance bottlenecks and propose innovative solutions.

Code Review and Testing:

• Conduct code reviews to ensure adherence to coding standards and best practices.

• Develop and execute test cases to validate functionality and performance.

Collaboration:

• Work closely with the software engineering and research teams to understand

requirements and deliver robust solutions.

• Provide technical guidance and mentoring to junior team members when necessary.

Documentation:

• Write and maintain technical documentation, including design specifications and user

manuals.

Required Skills:

• C++: Strong proficiency in modern C++ (C++11/14/17/20).

• CUDA Programming: Extensive experience in developing, debugging, and optimizing

CUDA applications.

• GPU Optimization: Familiarity with memory hierarchy, shared memory, streams, and

warp-level operations in CUDA.

• Parallel Computing: Solid understanding of parallel algorithms and multi-threaded

programming.

• Mathematical and Analytical Skills: Strong foundation in linear algebra, calculus, and

numerical methods.

• Tools: Experience with debugging/profiling tools like Nsight, CUDA Memcheck, or similar.

Job description:

• Hands on skills in Java programming languages
• Experience of testing of Cloud Native applications with exposure of Kafka.
• Understanding the concepts of K8, Caching, Rest / GRPC and Observability
• Experience with good programming or scripting practices and tools: code review, ADO/Jenkin etc
• Apply expertise in Java, API Testing, Cucumber or other test frameworks to design, develop and maintain automation test suites.
• Intimate familiarity with QA concepts: white-/black-/grey-box testing, acceptance/regression test, system integration test, performance/stress test, and security tests

Job Overview: 

We are seeking a skilled and experienced .NET Developer to join our development team. As a .NET Developer, you will be responsible for designing, coding, testing, and implementing software solutions using Microsoft technologies. 

Responsibilities:

• Collaborate with cross-functional teams to gather and define software requirements. 
• Design and develop robust, scalable, and high-performance applications using .NET technologies. 
• Write clean, well-documented, and efficient code following established coding standards.
• Perform thorough testing of the developed software to ensure the reliability and stability of applications. 
• Troubleshoot, debug, and resolve software defects and issues in a timely manner. 
• Stay updated on the latest trends and technologies in .NET development to enhance team knowledge and productivity. 
• Collaborate with other developers to review code, provide constructive feedback, and ensure code quality. 
• Participate in code and design reviews to maintain high development standards. 

Requirements: 

• Bachelor's degree in Computer Science, Information Technology, or related field. 
• Proven experience of 2-4 years as a .NET Developer or Software Developer. 
• Strong proficiency in C#, ASP.NET, and other .NET technologies. 
• Experience with front-end technologies such as HTML, CSS, and JavaScript. 
• Familiarity with databases (SQL Server, Oracle, or others) and data modeling. 
• Understanding of software development life cycle (SDLC) and best practices. 
• Excellent problem-solving and communication skills. 
• Ability to work both independently and collaboratively in a team environment. 
• Familiarity with Agile/Scrum methodologies is a plus. 

iOS Developer responsibilities include:

• Design and build applications for the iOS platform
• Ensure the performance, quality, and responsiveness of applications
• Collaborate with a team to define, design, and ship new features
•  Identify and correct bottlenecks and fix bugs
• Help maintain code quality, organization, and automatization
• Experience with iOS frameworks such as Swift UI, Objective C,
•  UIKit, AVFoundation, Core Bluetooth, Combine, PushNotifications.
•  Experience with Databases - Core Data, Realm  
•  Familiarity with RESTful APIs to connect iOS applications to back-end services
•  Knowledge of Architecture - MVC and MVVM
•  Understanding of Apple’s design principles and interface guidelines
•  Excellent communication Skills and Client interaction.

We are looking for IONIC Developers SDE |, SDE || & Lead positions "2-7 years"

Preferred Notice Period - Less Than 1 Month

Preferred Education - Tier 1 Engineering Colleges - IIT/NIT/DTU or similar

Preferred Work Background - Startup Engineering Experience

REQUIREMENTS

· 2-7 years of experience in Ionic version 3 and above

· A highly talented developer with hands-on experience with React.js, Angular, expert-level knowledge of JavaScript, TypeScript, CSS, HTML5, Bootstrap, Node.js, Web Services (REST) Working with MVVM, MVP, MVC patterns

· Knowledge on capacitor and Unit testing is must

· Familiarity with native build tools like Gradle for Android Studio, XCode

· Good understanding of asynchronous request handling, partial page updates, and AJAX Experience writing and maintaining automated unit-tests, functional tests

· Experience with creating and working with CI/CD pipelines

· Understanding of the full mobile development life cycle

· Knowledge of deployment process for both Android and iOS

· Proficient understanding of code versioning tools, such as (Git / Bitbucket)

· Ability to work independently with minimal supervision while achieving benchmarks Experience with Browser Dev Tools

· Strong written and oral communication. Nice to Have:

· Mobile app technologies such as React, React Native, Flutter

· Experience with PWA and SPAs

· Basic knowledge of image authoring tools, to be able to crop, resize, or perform small adjustments on an image. Familiarity with tools such as Gimp or Photoshop is a plus.

· Experience working in an Agile/Scrum development process

· Experience working with clients and teams in the US

RESPONSIBILITIES

· Focus on the delivery of web application development projects with heavy emphasis on responsive behavior.

· Work on all aspects of web products, including implementation of the design wireframes, animation/motion, business logic, interfaces to the backend APIs, incorporating analytics & SEO, performance and security.

· Work with the UI/UX designers, product and bridge the gap between Client requirements, graphical design and back-end interfaces.

· Take an active role in how the application looks as well as how it works Set a very high personal bar for code quality

· Build reusable code and libraries for future use

· Evaluate technical feasibility of UI/UX designs

· Optimize application for maximum speed and scalability

· Collaborate with other team members and stakeholders

· Create prototypes and POCs for internal and client use

· Stay updated in the state of the art in web technologies and bring new ideas and innovations to the projects

· Communicate technical issues in an understandable manner to the team and clients. Provide troubleshooting support to clients.

· Manual and automated unit testing to identify bugs and technical issues before and after deploying.

• Manage sales operations in assigned district to achieve revenue goals.
• Supervise sales team members; the BSMs, on daily basis and provide guidance whenever needed.
• Identify skill gaps and conduct trainings to sales team.
• Work with team to implement new sales techniques to obtain profits.
• Assist in employee recruitment, promotion, retention and termination activities.
• Conduct employee performance evaluation and provide feedback for improvements.
• Contact potential customers and identify new business opportunities.
• Stay abreast with customer needs, market trends and competitors.
• Maintain clear and complete sales reports for management review.
• Build strong relationships with customers for business growth.
• Analyze sales performances and recommend improvements.
• Ensure that sales team follows company policies and procedures at all times.
• Develop promotional programs to increase sales and revenue.
• Plan and coordinate sales activities for assigned projects.