Senior Software Professional - CRM, LMS & LOS Automation

🧭 Tech Lead (Backend / Fullstack | 7–10 Years)

Location: Bangalore (On-Site, Hybrid)

Company Type: Public-Listed Product Company

We’re Building a “Top 1% Engineering Org”

We’re building a high-talent-density, AI-first R&D organization from scratch — inside a publicly listed company undergoing a full-scale transformation.

Think:

→ Rewriting legacy systems into AI-native architectures

→ Embedding LLMs + Agentic AI into core workflows

→ Reimagining platforms, infra, and data systems for the next decade

This is the kind of shift you’d expect from Google, Microsoft, or Meta —

Except you get to build it from day 0 → scale it globally.

About the Role / Team

We are building a next-generation AI-first R&D organization in Bengaluru, focused on solving complex problems across LLMs, Agentic AI systems, distributed computing, and enterprise-scale architectures.

This initiative is part of a publicly listed global company investing heavily in AI-driven transformation, re-architecting its platforms into intelligent, autonomous systems powered by large language models, workflows, and decision engines.

You will be working on:

• Agentic AI systems & LLM-powered workflows
• Distributed, scalable backend systems
• Enterprise-grade AI platforms
• Automation-first engineering environments

🚀 The Mandate

Lead execution of mission-critical systems while staying hands-on — bridging architecture and delivery.

🧩 What You’ll Do

• Own end-to-end delivery of complex engineering initiatives (0→1, 1→N)
• Design systems across backend + frontend (if fullstack)
• Translate ambiguous problems into structured technical solutions
• Drive engineering best practices, code quality, and velocity
• Mentor engineers and elevate team performance
• Collaborate with stakeholders on roadmap and execution strategy

🧠 What We’re Looking For

• Strong experience in backend systems + optional frontend frameworks
• Proven ability to lead projects and deliver at scale
• Solid understanding of system design and architecture patterns
• Ability to balance speed vs quality vs scalability trade-offs
• Strong communication and leadership without authority
• Strong coding skills in Python / Java / Go / Node.js
• Solid understanding of data structures, system design basics, and backend architecture
• Experience building scalable APIs and services
• Familiarity or curiosity around AI/LLMs, async systems, or event-driven design
• Strong debugging, problem-solving, and ownership mindset

Nice to Have

• Experience integrating LLMs, vector databases, or AI pipelines
• Contributions to architecture at scale
• Experience with Agentic AI / LLM orchestration frameworks
• Background in product engineering or platform companies
• Exposure to global-scale systems (millions of users / high throughput)

🔥 What Sets You Apart

• Experience leading platform builds or major system rewrites
• Exposure to AI systems, LLM integrations, or intelligent workflows
• Built platforms used by millions of users / high-throughput systems
• Experience with event-driven systems, stream processing, or infra platforms
• Prior work on AI/ML platforms, model serving, or intelligent systems

Background: We Commonly See (But Not Limited To)

• Our team often includes engineers from top-tier institutions and strong research or product company or DeepTech or AI Product backgrounds, including:
• Leading engineering schools in India and globally
• Engineers with experience in top product companies, AI startups, or research-driven environments
• That said, we care far more about demonstrated ability, depth, and impact than pedigree alone.

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

Company: Kredit Venture

About the company:

KreditVenture is seeking a Technical Product Manager to lead the development, strategy, and

execution of our SaaS applications built on top of Loan Origination Systems and Lending Platforms.

This role requires a strong technical background, a product ownership mindset, and the ability to

drive execution through both in-house teams and outsourced vendors. The ideal candidate will play

a key role in aligning business goals with technical implementation, ensuring a scalable, secure,

and user-centric platform.

Job Description

Job Title: Senior Manager / AVP / DVP – Technical Product Manager

Location: Mumbai (Ghatkopar West)

Compensation: Upto 25 LPA

Experience: 7-8 years (Designation will be based on experience)

Qualification: 

- Bachelor’s degree in Computer Science, Engineering, or a related field.

- An MBA is a plus.

 Roles and Responsibilities

Technology Leadership:

• Lead SaaS Platform Development – Strong expertise in full-stack development (Java, Python, MERN stack) and cloud-based architectures.
• API & Workflow Design – Drive microservices-based REST API development and implement business process automation.
• Third-Party Integrations – Enable seamless API integrations with external service providers.
• Code Quality & Best Practices – Ensure code quality, security, and performance optimization through structured audits.

Vendor & Delivery Management:

• Outsourced Vendor Oversight – Manage and collaborate with external development partners, ensuring high-quality and timely delivery.
• Delivery Governance – Define SLAs, monitor vendor performance, and proactively escalate risks.
• Quality Assurance – Ensure vendor deliverables align with product standards and integrate smoothly with internal development.

Collaboration & Stakeholder Engagement:

• Customer Insights & Feedback – Conduct user research and feedback sessions to enhance platform capabilities.
• Product Demos & GTM Support – Showcase platform features to potential clients and support sales & business development initiatives.

Platform Development & Compliance:

• Component Libraries & Workflow Automation – Develop reusable UI components and enable no-code/low-code business workflows.
• Security & Compliance – Ensure adherence to data protection, authentication, and regulatory standards (e.g., GDPR, PCI-DSS).
• Performance Monitoring & Analytics – Define KPIs and drive continuous performance optimization.

Job Description:

Responsibilities:

·      Participate in the entire application lifecycle, focusing on coding and debugging

·      Ability to design and document the product features, codes.

·      Self-driven and ability to take up ownership of things

·      Write clean code to develop functional applications, automation scripts, test cases

·      Troubleshoot and debug applications

·      Collaborate with developers, cross-functional teams to identify issue, new features and come up with solutions

·      Gather and address technical and design requirements

·      Provide training and support to internal teams

·      Build reusable code and libraries for future use

·      Ability to sync with other developers, designers to identify issues, new features and improvements

Requirements and skills:

·      Solid understanding of linux development environment and systems

·      Expert level knowledge of Python along with frameworks like Django, flask

·      Proficient in writing unit test cases using Pytest framework.

·      Expert level knowledge of SQL databases like MySQL and PostgreSQL

·      Good knowledge of design principles and databases

·      Knowledge of front technologies like Typescript, ReactJs

·      Knowledge of Caching techniques using Memcached and Redis

·      Experience of using queueing service line Kafka

·      Solid understanding of microservices architecture

·      Knowledge of AWS cloud services

·      Expert in serverless technologies like lambda along with API gateway

·      Knowledge of Git, Jira, CI/CD pipelines and containerization like docker

·      Knowledge of logging and monitoring tools like Grafana or Newrelic

About Us

UnScript.AI is a Deep-Tech company with a focus on creating highly engaging interactive videos solving conversion and engagement problems leveraging the most recent breakthroughs in Artificial Intelligence.

Responsibilities:

Full Stack Engineers at UnScript.AI are involved in all parts of the product life cycle: idea generation, design, planning, execution, and shipping. On day-to-day work, we create reliable, scalable and highly performant systems. A commitment to teamwork, hustle and good communication skills are our key requirements. As Full Stack Engineer, you will lead end-to-end development of modules with complete ownership of design, planning, coding & delivery.

• The Software Development Engineer's core responsibilities include working on highly maintainable and unit-tested software components/systems that address real-world problems.
• Ensure quality at every level be it problem-solving, design, code or bug fixes.
• Should be able to collaborate with product managers, architects and other stakeholders to ensure smooth execution of sprints.
• Own and unblock users on production issues, able to troubleshoot and fix production issues on priority.

SKILL SETS REQUIRED: Kubernetes, AWS/any other cloud, NodeJS, JavaScript, React/Next, Design thinking, API Framework

REQUIRED QUALIFICATIONS

• B.Tech or higher in Computer Science from a premier institute. (We are willing to waive this requirement if you are an exceptional programmer).

• You are a strong coder, Love to explore multiple languages and tech stacks; We are language-agnostic, and we love people who like to explore multiple stacks. We’re looking for people who can write clean, effective code.

• Building scalable & performant web systems with clear focus on reusable modules.

• You are comfortable in a high paced environment and can respond to urgent (and at times ambiguous) requests

• Ability to translate fuzzy business problems into technical problems & come up with design, estimates, planning, execution & deliver the solution independently.

Follow Agile development model to incrementally build out the applications with regular reviews with Product

• Knowledge in AWS would be great to have.

• Ability to work with databases, data pipelines.

About Us:

UnScript is a deep tech startup that builds powerful SAAS tool to generate videos using AI. UnScript was founded by distinguished alums from IIT, with exemplary backgrounds in business and technology. UnScript has raised two rounds of funding from global VCs with Peter Thiel(Co-founder, Paypal) and Ried Hoffman ( Co-founder, Linkedin) as investors. 

The Team:

Unscript was started by Ritwika Chowdhury. Our team brings experience from other foremost institutions like IIT Kharagpur, Microsoft Research, IIT Bombay, IIIT, BCG etc. We are thrilled to be backed by some of the world's largest VC firms and angel investors. 

Online tutoring platform that focuses on connecting students with tutors and has a focus on live learning courses for Science, Technology, Engineering, the Arts and Mathematics (STEAM) subjects. It is a global online school for 21st century skills, teaching Coding and other extra-curriculars to kids age 5-18 via LIVE, interactive, gamified online sessions that work 10x better than status quo.

• 2+ years of experience on NodeJS & React JS
• Practical experience in building APIs
• Experience with RabbitMQ or similar queuing system
• Experience with Redis/ElasticSearch is a plus
• Familiarity with CI/CD pipeline tools like Jenkins
• Practical experience with Git
• A knack for benchmarking and optimization

What you need to have:

• Strong experience in WooCommerce – Able to create easy and complex plugins, shortcodes, and widgets
• Exposure to a minimum of 3 e-commerce projects (starting with requirement gathering).
• Expert in WordPress, and other CMS platforms.
• Should have experience of working on large projects involving 10,000+ products.
• Experience in developing E-Commerce websites.
• Strong knowledge in WordPress Plugin, and PHP.
• Must have experience of building User Interfaces and Prototypes.
• Experience designing and developing responsive design websites.
• Comfortable working with debugging tools like Firebug, Chrome inspector, etc.
• Good with third-party integrations to CRM, ERP, etc.
• Knowledge of code versioning tools including Git and Bitbucket.
• Strong Experience in MySQL and Database Queries.

Experience: 2 to 5 years

Annual CTC: Rupees 4,00,000 to 6,00,000

You are required to possess good knowledge of PHP and experience in Laravel repository.

Responsibilities and Duties:

• Work alongside a broader team with a focus on Design, UX, Optimization, Back End processes, DevOps Efficiency with the goal of delivering high-quality projects using the latest tech stack.
• A keen eye for detail, along with a passion to deliver quality, customer-focused solutions is absolutely essential.
• Championing Web Development: You will be responsible for handling web development from ideation to production.
• Collaboration with product manager and other developers, owning a large part of the process from problem understanding to shipping the solution.
• Contribute best-in-class programming skills to develop highly innovative, consumer-facing web products.

Key Skills:

PHP MVC Framework Laravel, API Integration and Development, HTML5, CSS3, JavaScript, Version Control Systems, Repository Management, Basic understanding to work on AWS 

Required Experience and Qualifications:

Desired Profile:

• Great skills in PHP MVC framework Laravel.
• Extensive Experience in API integration and development is required.
• Experience in HTML5, CSS3, and JavaScript is required.
• Experienced with version control systems and repository management.
• Experience working and configuring AWS is a huge plus. but a basic understanding to work on AWS is required.
• Passionate about writing clean, efficient, and maintainable code.
• Strong analytical and debugging skills and experience building consumer systems at scale.