SDET/Automation Developer

Roles & Responsibilities

• Design and conduct quantitative UX research studies to evaluate user behavior and product usability.
• Plan, execute, and analyze A/B tests and controlled experiments.
• Define research objectives, hypotheses, success metrics, and measurement frameworks.
• Analyze product metrics, user engagement, conversion funnels, retention, and feature adoption.
• Extract and analyze data using SQL and product analytics tools.
• Use statistical methods to validate research findings, including sample size calculations, confidence intervals, and statistical significance testing.
• Collaborate with Product Managers, UX Designers, Data Analysts, and Engineering teams to support product strategy.
• Create dashboards, reports, and presentations to communicate research findings and recommendations.
• Identify user behavior patterns and opportunities for product optimization.
• Translate complex quantitative insights into clear, business-focused recommendations.
• Support product development by measuring the impact of new features and product improvements.
• Stay updated with industry trends, research methodologies, and analytics best practices.

Ideal Candidate

• Strong understanding of experimental design and statistical methodologies.
• Hands-on experience with SQL and product analytics platforms such as Amplitude, Mixpanel, or GA4.
• Ability to interpret large datasets and generate actionable business insights.
• Excellent problem-solving, analytical thinking, and stakeholder communication skills.
• Passion for improving user experience through data-driven decision-making

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

What You will do

We're looking for bright Senior DevOps engineers that are deeply experienced individual contributors and dynamic team leaders, to join our dedicated DevOps Practice Group. As a Senior DevOps practitioner at Zemoso you’ll use your expertise to provide DevSecOps services to our customers and to our inhouse Dev teams.

Basic Qualifications

• Bachelor's degree in computer science, engineering or equivalent experience. 
• 15+ years of overall IT experience
• 10+ years of DevOps experience with 5+ years of it on Azure platform
• Relevant Azure Certification(s)

Must have experience

• IaC tools ARM/bicep template, Azure DevOps
• GITHub repo and GIT tools
• scripting languages Python, PowerShell, bash development experience
• CI/CD design, build management.
• Container tools Docker and Kubernetes
• Azure Policy and permissions provisioning.
• IT experience to design, development (Java Spring Boot), automated testing, REST API’s, Microservices, Pub/Sub architecture
• Costing, budgeting, forecasting, monitoring cloud expenses.
• Architecture drawings and proposals, presentations.
• Stakeholder management.
• Prototyping.

Nice to have experience

• IaC tools CloudFormation, Terraform 
• Build tools Apache Maven, Jenkins
• Networking: DNS, TCP/IP, HTTP, CDN and VPN
• Security: NSG, firewall and Azure policies, HTTPS, SSL certificates, KMS key
• Authentication (IAM): SAML 2.0, OpenID Connect, OAuth 2.0, Keycloak-based IdAM, LDAP and AD, and/or 3rd-party SSO.
• Access: RBAC and ABAC
• Load Balancers: Apache, Nginx, HAProxy
• Encryption: PKI infrastructure, Certificate authorities, OCSP, CRL, CSRs, x.509 certificate structures, pkcs12 certificate containers

Additionally, we’re looking for individuals who:

• Will assist in the rollout and deployment of new product features, and deploy applications via automation with configuration management tools
• Will build applications and tools to reduce barriers, decrease friction and speed up delivery of products
• Can effectively articulate technical challenges and solutions.
• Have strong collaborative instincts and interpersonal skills; must enjoy and work well with a wide variety of stakeholders in a complex organization
• Will manage individual project priorities with guidance, meeting deadlines and deliverables.

Benefits

• Competitive salary.
• Work from anywhere.
• Learning and gaining experience rapidly.
• Reimbursement for basic working set up at home.
• Insurance (including a top up insurance for COVID).

Location

Remote - work from anywhere.

About us:

Zemoso Technologies is a Software Product Market Fit Studio that brings silicon valley style rapid prototyping and rapid application builds to Entrepreneurs and Corporate innovation. We offer Innovation as a service and work on ideas from scratch and take it to the Product Market Fit stage using Design Thinking->Lean Execution->Agile Methodology.

We were featured as one of Deloitte Fastest 50 growing tech companies from India thrice (2016, 2018 and 2019). We were also featured in Deloitte Technology Fast 500 Asia Pacific both in 2016 and 2018.

We are located in Hyderabad, India, and Dallas, US. We have recently incorporated another office in Waterloo, Canada.

Our founders have had past successes - founded a decision management company acquired by SAP AG (now part of Hana Big data stack & NetWeaver BPM), early engineering team of Zoho (leading billion $ SaaS player) & some Private Equity experience.

Marquee customers along with some exciting start-ups are part of our clientele.

• Familiarity with the http://asp.net/">ASP.NET framework, SQL Server and design.
• Hands on experience using C# .NET, MVC, Oops Concept, Jquery, Bootstrap.
• Knowledge of  .NET languages 
• Familiarity with architecture styles/APIs (REST, RPC)
• Understanding of Agile methodologies
• Strong attention to detail
• Excellent troubleshooting and communication skills
• Knowledge of REST and RPC APIs
• Angular will be an advantage
• Able to work well in a team setting

• Bachelor’s Degree in Computer Science or equivalent
• 8-12 years’ of industry experience in programming web applications, mobile and/or large scale enterprise products
• Deep knowledge of C#, ASP, .NET, MVC, .Net core
• Deep knowledge and extensive experience working on Ruby or React and JavaScript, as required
• Experience with XML, ADO/ADO.NET, LINQ, AJAX, IIS
• Extended experience with SQL, relational and non-relational databases
• Experience in TFS and Visual Studio
• Hands on experience with SDLC and programming design patterns
• Experience with Agile methodology
• Skillful at reviewing new feature impact on an application and recognizing potential risks
• Uses time effectively and efficiently
• Quickly learns new technologies
• Detailed oriented, professional and possesses a positive work attitude
• Communicate professionally both verbally and in writing
• Effective time management skills
• Knowledge on UI technologies will be plus

PRINCIPAL DUTIES AND RESPONSIBILITIES:

• Develops software solutions by studying information needs, conferring with users, studying systems flow, data usage, and work processes, investigating problem areas, following the software development lifecycle.
• Conducts systems analysis and makes recommendations to improve the system to achieve an outcome.
• Promotes internal best practices and coding conventions to write and execute tests for your own code, including creating comprehensive unit tests.
• Contributes to Technical Requirements Documents.
• Requests constructive feedback for designs early in the process.
• Communicates successfully with large teams and many stakeholders.
• Provides mentorship for Software Engineers and participates in interview panels to hire new Software Engineers.
• Assists in removing obstacles for the team to yield successful sprints.
• Performs peer code reviews to ensure quality of the codebase.
• Ability to decompose and delegate work to junior engineers.
• Updates job knowledge by studying state-of-the-art development tools, programming techniques and computing equipment; participating in educational opportunities, reading professional publications, maintaining personal networks, participating in professional organizations.
• Works effectively with multiple projects and features.
• All other duties as assigned.

Out of many tools and technologies, we use Java, MongoDb, Cassandra, Redis, Twem, Netty extensively for our back-end development.

• Leading the entire Backend platform for a product portfolio.
• End to end delivery new features.
• Evolving the architecture for performance and scalability.
• Design, develop and own components of a highly scalable, distributed web services platform.
• Constantly strive to improve software development process and team productivity.
• Mentor and train team members
• Lead module development independently

Required background, Knowledge, Skills and Abilities

• 5.5+/ 7+ Years of experience in a scalable product/ecommerce organization·       
• Excellent Java skills, Understanding of Spring framework & MVC approach
• Strong knowledge of Performance optimization and caching techniques.
• Strong Object Oriented Programming concepts, data structure and algorithms
• Experience in developing scalable, fault-tolerant, distributed backend services
• Experience with prevalent design patterns and advanced system designing
• Good experiences with databases and Schema design. We heavily use NoSQL databases
• Strong Problem Solving skills

Main Priorities:

Experienced in Installation, Configuration and Maintenance of Microfocus EMS tool. Operational Knowledge on below mentioned modules is a must.

Network Node Manager

Network Automation

Operations Bridge Management

Service Management

Universal Discovery

ZENworks Configuration Management

ZENworks Patch Management