Lead AI / Machine Learning expert

About Us

We believe the future of software development is AI-native — where engineers operate at a higher level of abstraction and quality remains non-negotiable. 

Incubyte is a software craft consultancy where the “how” of building software matters as much as the “what”.  

We partner with companies of all sizes, from helping enterprises build, scale, and modernize to early-stage founders bring their ideas to life. 

Our engineers operate in an AI-native development model, using AI as a collaborator across the SDLC to accelerate development while upholding the discipline of software craftsmanship. Guided by Software Craftsmanship and Extreme Programming practices, we build reliable, maintainable, and scalable systems with speed, without compromising quality. If this way of building software resonates with you, we’d like to talk. 

Our Guiding Principles 

These principles define how we work at Incubyte. They are non-negotiable. 

Relentless Pursuit of Quality with Pragmatism 

 We build high-quality systems without losing sight of delivery. 

Extreme Ownership 

 We take responsibility end-to-end for decisions, execution, and outcomes. 

Proactive Collaboration 

 We collaborate closely, challenge each other, and solve problems together. 

Active Pursuit of Mastery 

 We continuously improve our craft and raise our bar. 

Invite, Give, and Act on Feedback 

We seek, give, and act on feedback to get better every day. 

Ensuring Client Success 

We act as trusted partners and focus on real outcomes, not just output. 

Job Description

This is a remote position.

This is a remote position.

Experience Level

This role is ideal for engineers with 3–6 years of experience and a strong background in building scalable, production-grade software systems.

We are looking for hands-on Software Engineers with deep expertise in Python and TypeScript, with exposure to AI/LLM systems and modern infrastructure tooling.

What You’ll Do as a Software Craftsperson

•     Take full ownership of the software development lifecycle for complex, cross-functional initiatives — from design through production readiness.

•     Build and maintain robust, scalable backend systems and APIs using Python and TypeScript, following clean code and software craftsmanship principles.

•     Design and deliver features end-to-end, balancing scope, quality, and long-term maintainability.

•     Identify technical and product issues beyond the immediate scope of work, proactively raising risks and driving solutions.

•     Shape team practices around code quality, testing, tooling, and continuous improvement using DevEx and DORA principles.

•     Collaborate closely with clients and internal teams to understand requirements, clarify priorities, and align on outcomes.

•     Mentor and guide fellow engineers to raise overall team performance and promote a culture of learning.

•     Leverage AI tools (LLMs, agentic frameworks, etc.) to accelerate design, development, testing, and delivery where applicable.

Requirements

What You’ll Bring

3–6 years of overall software engineering experience with a strong track record of owning and delivering complex production systems.

Must-Have Skills

•     Python (must-have): Deep expertise in writing idiomatic, testable, production-grade Python — including advanced OOP, data structures, algorithms, and software engineering best practices.

•     TypeScript (must-have): Strong proficiency in building and maintaining type-safe, scalable applications across frontend and/or backend TypeScript codebases.

•     Strong system design skills: ability to architect scalable, maintainable, and observable systems with a focus on reliability and long-term operability.

•     Solid engineering practices: experience with TDD, CI/CD, code reviews, refactoring, and continuous deployment in Agile or eXtreme Programming environments.

•     Working knowledge of relational databases, web server ecosystems, REST/gRPC APIs, and performance optimisation.

•     Experience with source control, bug tracking, user story writing, and maintaining clear technical documentation.

Good-to-Have Skills

•     AI / LLM experience: hands-on exposure to building applications using LLMs (GPT, Claude, Gemini, or similar) for tasks such as document classification, entity extraction, or structured data generation.

•     LLM orchestration frameworks: familiarity with LangChain, LlamaIndex, Mastra, Agno, or similar agentic frameworks.

•     Prompt engineering: experience refining prompts and orchestration patterns to improve response accuracy, consistency, and structured outputs.

•     Vector databases and observability tooling: exposure to tools like Pinecone, PgVector, Qdrant, LangSmith, or DeepEval.

•     Container orchestration and infrastructure-as-code: experience with Kubernetes, Terraform, and Docker for deploying and managing production workloads.

Benefits

Life at Incubyte

We are a remote-first company with structured flexibility. Teams commit to shared rhythms during core hours, ensuring smooth collaboration while maintaining autonomy. Twice a year, we come together in person for a co-working sprint and once a year for a retreat — with all travel expenses covered.

Our environment is built for crafters: experimenting with real-world systems, solving complex infrastructure challenges, and contributing to cutting-edge AI initiatives. We are all lifelong learners, and our work is our passion.

Perks

•     Dedicated learning & development budget

•     Sponsorship for conference talks

•     Comprehensive medical & term insurance

•     Employee-friendly leave policies

•     Home Office fund

•     Medical Insurance

Job Description: Tech Lead – AI & Technology

Role Title: Tech Lead – AI & Technology

Location: Bangalore, India – Fully On-site

Experience: 5+ Years

Employment Type: Full-time

About the Role

We are looking for an experienced and hands-on Tech Lead to lead a small engineering team and drive the development of AI-powered applications, internal technology platforms, and modern IT solutions. The Tech Lead will be responsible for technical direction, architecture, development, code quality, team management, and end-to-end delivery of technology projects. The ideal candidate should have strong programming experience, particularly in Python and ReactJS, along with practical experience working with AI/ML technologies.

1. Technical Leadership & Team Management

• Lead and mentor a team of developers and technical team members.
• Own technical delivery across multiple projects and initiatives.
• Assign tasks, review progress, resolve technical blockers, and ensure timely delivery.
• Conduct code reviews and establish engineering best practices.
• Mentor team members and support their technical growth.

2. Software Development & Architecture

• Design and develop scalable, secure, and maintainable applications.
• Lead backend development using Python and frontend development using ReactJS.
• Define application architecture, technology choices, APIs, integrations, and development standards.
• Review technical designs and ensure high-quality implementation.
• Troubleshoot complex technical issues and drive effective solutions.

3. AI & Technology

• Lead the development and integration of AI-powered applications and solutions.
• Work with AI/ML models, APIs, LLMs, Generative AI, and related technologies.
• Evaluate emerging AI tools and technologies and identify opportunities for practical implementation.
• Collaborate with product and business teams to translate requirements into AI-enabled technology solutions.

4. Project Delivery

• Own the complete technology lifecycle from requirements and architecture to development, testing, deployment, and maintenance.
• Plan sprints, estimate development efforts, and track technical milestones.
• Work closely with cross-functional stakeholders to understand requirements and deliver solutions.
• Ensure projects meet timelines, quality standards, security requirements, and performance expectations.

5. Engineering Quality & Infrastructure

• Establish standards for coding, testing, documentation, version control, and deployment.
• Ensure applications are scalable, reliable, and secure. l Collaborate on cloud infrastructure, APIs, databases, CI/CD, and deployment processes.
• Identify opportunities to improve system performance and engineering efficiency.

Technical Skills – Must Have

• 5+ years of software development experience.
• Strong hands-on experience with Python.
• Strong experience with ReactJS / React.
• Experience leading or managing technical team members.
• Strong understanding of AI/ML and Generative AI technologies.
• Experience with APIs, databases, Git, and software development lifecycle.
• Strong understanding of application architecture and system design.
• Experience building and deploying production-grade applications.

Technical Skills – Good to Have

• Experience with LLMs, RAG, AI agents, or Generative AI applications.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with Docker, CI/CD, and DevOps practices.
• Experience integrating third-party AI APIs and services.
• Experience working in startups or fast-paced technology environments.

What We Are Looking For

• Strong technical ownership and problem-solving ability.
• Ability to balance hands-on coding with team leadership.
• Excellent communication and stakeholder management skills.
• Ability to mentor developers and drive accountability within the team
• Strong interest in AI and emerging technologies.
• A proactive, ownership-driven approach with the ability to work in a fast-paced environment.

Why Join Us?

• Work on AI-powered technology with meaningful social impact.
• Lead a small, high-ownership technology team.
• Work across AI, software engineering, and modern IT infrastructure.
• Opportunity to shape technology architecture and engineering practices from the ground up.
• Collaborative and fast-moving environment with significant technical ownership.

Click "Apply Now" in https://gosuperedtech.com/career/ai-system-engineer to apply

Role Overview

We are looking for a Junior AI System Engineer who is eager to build a career in AI systems, automation, backend workflows, cloud infrastructure, and intelligent product operations.

This role offers an opportunity to work closely with experienced engineers, product teams, and AI specialists on real AI-powered systems that support learners, educators, schools, and internal business operations.

At GoSuper EdTech, our cloud infrastructure is built on Google Cloud Platform — GCP. You will get hands-on exposure to GCP-based systems, backend services, AI integrations, deployment workflows, monitoring, cloud storage, databases, and automation pipelines.

You will help design, integrate, test, monitor, and maintain AI-enabled systems using modern tools such as AI APIs, LLMs, automation workflows, backend services, databases, GCP services, cloud deployment tools, and monitoring systems.

This role is ideal if you are curious about AI, comfortable with technical problem-solving, and interested in building reliable systems that connect software, data, cloud infrastructure, automation, and intelligent workflows.

What You’ll Do

• Support the development and maintenance of AI-powered systems, tools, and workflows.
• Assist in integrating AI APIs, LLM platforms, automation tools, and backend services into GoSuper products.
• Work with OpenAI, Gemini, Claude, or similar AI platforms under the guidance of senior engineers.
• Support AI and backend workflows deployed on Google Cloud Platform — GCP.
• Assist with GCP-based services such as Cloud Run, Compute Engine, Cloud Functions, Cloud Storage, Firebase, Firestore, Cloud SQL, BigQuery, Pub/Sub, Cloud Logging, and Cloud Monitoring, based on project needs.
• Help build AI workflows for content generation, chatbot systems, smart recommendations, internal automation, and productivity tools.
• Support backend integrations using Node.js, Python, REST APIs, webhooks, and third-party services.
• Assist in designing and maintaining system workflows that connect databases, applications, AI models, cloud services, and business tools.
• Work with databases such as PostgreSQL, MongoDB, Firebase, Firestore, Supabase, or similar platforms.
• Help test AI outputs, validate workflows, debug issues, and improve system reliability.
• Monitor system performance, API usage, errors, logs, workflow failures, and cloud service health.
• Support deployment, configuration, and maintenance of AI-enabled product features on GCP.
• Collaborate with product managers, developers, designers, QA teams, and business teams to understand requirements and deliver working solutions.
• Participate in daily standups, sprint planning, technical discussions, and team meetings.
• Document AI workflows, system logic, API integrations, prompts, GCP configurations, deployment steps, and troubleshooting processes.
• Continuously learn and apply best practices in AI systems, backend engineering, automation, GCP cloud infrastructure, and production support.

What We’re Looking For

• 6 months to 1 year of experience in AI systems, backend development, software engineering, automation, DevOps support, cloud support, system integration, or relevant internship/project experience.
• Basic understanding of AI tools, LLMs, APIs, automation workflows, and software systems.
• Working knowledge of JavaScript, TypeScript, or Python.
• Basic backend development experience with Node.js, Express, NestJS, FastAPI, or similar frameworks.
• Basic understanding of Google Cloud Platform — GCP or willingness to learn GCP-based deployment and monitoring workflows.
• Understanding of REST APIs, webhooks, third-party integrations, and data flow between systems.
• Interest in AI APIs, prompt workflows, chatbot systems, automation tools, and intelligent product features.
• Basic understanding of databases such as PostgreSQL, MongoDB, Firebase, Firestore, Supabase, or Redis.
• Ability to debug technical issues across APIs, workflows, logs, backend services, and cloud deployments.
• Good analytical thinking and problem-solving ability.
• Ability to write clear documentation for workflows, integrations, cloud configurations, and technical processes.
• Eagerness to learn new tools, AI platforms, system design concepts, GCP services, and cloud technologies.
• Good communication skills to work with technical and non-technical teams.
• Ownership mindset and willingness to take responsibility for assigned tasks.
• Comfortable working in a fast-paced startup environment.

Nice to Have

• Familiarity with AI APIs such as OpenAI, Gemini, Claude, or similar platforms.
• Basic understanding of prompt engineering and LLM-based workflows.
• Exposure to LangChain, LlamaIndex, embeddings, vector databases, or retrieval-augmented generation.
• Basic experience with GCP services such as Cloud Run, Cloud Functions, Firebase, Firestore, Cloud Storage, Cloud SQL, BigQuery, Pub/Sub, Cloud Logging, or Cloud Monitoring.
• Exposure to Google AI tools, Vertex AI, Gemini API, or AI-related services on GCP.
• Experience with automation tools, workflow builders, webhooks, or integration platforms.
• Exposure to Docker, CI/CD pipelines, GitHub Actions, deployment workflows, or cloud-based release processes.
• Experience working with logs, monitoring tools, API testing tools, or debugging platforms.
• Familiarity with Postman, Git, GitHub, Notion, Zoho, Slack, or similar productivity tools.
• Experience building chatbots, AI assistants, internal tools, or automated workflows.
• Personal, academic, internship, or open-source projects related to AI, automation, backend systems, GCP, or cloud tools.
• Interest in SaaS, EdTech, AI-powered products, and startup environments.

What You’ll Gain

• Hands-on experience building AI-powered systems in a real startup environment.
• Practical exposure to AI APIs, LLM workflows, automation systems, backend services, and GCP cloud infrastructure.
• Mentorship from senior engineers and product leaders.
• Experience working across AI, backend engineering, databases, APIs, integrations, deployment, system monitoring, and cloud operations.
• Opportunity to contribute to real product features used by learners, educators, schools, and institutions.
• Exposure to SaaS product development, EdTech workflows, AI-driven business solutions, and GCP-based production systems.
• Learning culture that encourages experimentation, feedback, and continuous improvement.
• Opportunity to understand how AI systems are designed, deployed, monitored, scaled, and improved in production.
• Access to Cult Elite and Cult Play Pass, offering wellness and lifestyle benefits to keep you energized and inspired.

Compensation

• Competitive salary with performance-based bonuses.
• Equity ownership through ESOPs — own a piece of the company you help build.
• Flexible remote work options with occasional Bengaluru office meetups.
• Health and wellness perks, including Cult Elite membership and Cult Play Pass for employees.
• Learning and development support to help you grow in AI systems, backend engineering, automation, SaaS, and GCP cloud technologies.
• Team retreats, virtual hangouts, and a collaborative work culture.

We are looking for a AI System Engineer who is eager to build a career in AI systems, automation, backend workflows, cloud infrastructure, and intelligent product operations. Apply in https://gosuperedtech.com/career/ai-system-engineer

Role & Responsibilities

Responsibilities

• Business: Immerse in operations until you think like an insider.

Rapidly acquire domain expertise through direct observation, translate between business and engineering seamlessly, and mentor engineers in your area on immersion. Influence senior stakeholders effectively, manage complex stakeholder landscapes with competing agendas, and build trust rapidly with new stakeholders.

• Delivery: Lead rapid delivery initiatives across teams in your area, coach on prototype-first approaches, and establish trust through consistent fast delivery. Build complete applications rapidly across any technology stack, select the right tools for each problem, and define clear criteria for prototype-to-production transitions.

• Generative AI: Architect RAG systems for complex use cases across teams, implement advanced techniques (hybrid search, reranking, query expansion), mentor engineers on RAG best practices, and establish RAG standards. Lead evaluation strategy across teams, establishing annotation guidelines, training human-calibrated LLM judges, and building evaluation pipelines that connect tracing to datasets to experiments.

• People: Build high-performing teams across your area, navigate complex interpersonal dynamics, foster psychological safety, and create environments where diverse perspectives are valued. Influence through communication at all levels — from frontline to executive. Handle difficult conversations skilfully and train engineers in your area on effective communication.

• AI-Augmented Development: Optimise AI tool usage across teams in your area, train engineers on AI-augmented and agentic engineering workflows, evaluate new AI development tools, and establish practices that balance AI speed with verification rigour.

• Scale: Design complex multi-component systems end-to-end, evaluate architectural options for large initiatives across teams, guide technical decisions for your area, and mentor engineers on architecture. Create debt reduction strategies across teams, influence roadmap decisions to include debt work, and teach engineers when to accept debt for speed versus when to invest in quality.

• Documentation: Define documentation standards across teams in your area, create documentation systems and templates, train engineers on spec-driven development, and ensure documentation quality across projects. Lead pattern generalization initiatives, defining criteria for when to generalize versus keep custom.

• Reliability: Define reliability standards across teams in your area, drive post-incident improvements systematically, design capacity planning processes, andmentor engineers on SRE practices.

Ideal Candidate

• Strong Staff Software Engineer / FDE profile (full-stack + production GenAI, multi-team technical leadership)
• Mandatory (Experience 1) – Must have 7+ years of relevant professional software engineering experience, with demonstrated full-stack delivery across backend and frontend.
• Mandatory (Experience 2) – Must have deep production experience with Python AND JavaScript/TypeScript, working comfortably across the full stack.
• Mandatory (Experience 3) – Must have 2+ years of experience in generative AI applications developement — LLM integrations, vector databases, RAG systems, and evaluation pipelines
• Mandatory (Experience 4) – Must have strong experience with modern frontend frameworks (Next.js / React) and backend API development.
• Mandatory (Experience 5) – Must have extensive experience with cloud platforms (AWS preferred; Azure/GCP valued), including infrastructure-as-code (CloudFormation / Terraform).
• Mandatory (Experience 6) – Must have working knowledge of multiple database paradigms — relational (PostgreSQL), document, and key-value (Redis) — with ability to select the right storage per problem.
• Mandatory (Experience 7) – Must have strong experience with CI/CD pipelines (e.g. GitHub Actions), containerization, and production deployment strategies.
• Mandatory (Experience 8) – Must have demonstrable fluency with AI coding tools (Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on them
• Preferred (Experience) – Advanced RAG techniques — hybrid search, reranking, query expansion — and establishing RAG standards across teams

Job Title: Software/Hardware Engineer (IIT/NIT)

Location: Bangalore

Website: https://www.zeuron.ai

Experience: 1-5Years

CTC: 6-10 LPA

No Freshers

About the Company

Zeuron.ai is a Bangalore-based deep-tech startup founded in 2019, focused on building brain-inspired computing and AI-driven healthcare solutions. The company combines neuroscience, AI, and gaming to create innovative digital therapeutics and neurotechnology platforms for improving brain health, rehabilitation, and overall well-being.

The role

Zeuron.ai is looking for hands-on software engineers who can turn an incomplete brief into reliable, usable software. You will work as an individual contributor, make sound technical decisions and take responsibility for the quality of what you deliver.

AI coding tools will be part of the workflow. We expect you to understand the underlying software well enough to build and debug without an LLM, then use AI to accelerate implementation, exploration and verification. You remain accountable for the result.

What you will own

• End-to-end delivery: clarify requirements, break work into achievable steps, implement features, test them, deploy them and respond to issues after release.

• Product decisions: understand the user problem, question unclear requirements and explain trade-offs between speed, quality, complexity and maintainability.

• Reliable software: investigate defects, identify root causes and improve error handling, performance and usability.

• Engineering continuity: maintain readable code, useful documentation and clear handovers so that others can run, understand and extend your work.

Engineering expectations

We value demonstrated building ability, technical reasoning and sound judgement. Tool familiarity should be supported by evidence of software you have actually delivered.

Software fundamentals

• Programming: practical fluency in at least one programming language, with an understanding of data structures, control flow, modularity and common complexity trade-offs.

• Applications and services: understand how interfaces, APIs, business logic and data storage interact. Be able to trace a failure across these boundaries.

• Data: work with databases, reason about data models and queries, and handle validation, consistency and errors appropriately.

• Development workflow: use Git confidently, review changes, manage dependencies and keep development and deployment instructions reproducible.

• Testing and debugging: reproduce failures, form hypotheses, inspect logs and isolate causes. Test important behaviour and edge cases rather than relying on a successful demo.

• Security and reliability: recognise basic risks around authentication, access control, secrets, input handling and third-party dependencies.

Build independently. Use AI effectively.

• Without LLMs: write and modify code, diagnose defects, explain design choices and use documentation to solve unfamiliar problems independently.

• With AI coding tools: frame tasks clearly, supply relevant context, use generated suggestions selectively and inspect the resulting changes.

• Verify before accepting: check correctness, integration, security and maintainability. Recognise invented APIs, fragile assumptions and plausible-looking code that does not solve the actual problem.

• Protect information: use approved tools and handle credentials, proprietary code and user data responsibly.

Evidence we want to discuss

Be prepared to walk through a project you contributed to: the problem, your specific contribution, important technical decisions, a difficult bug and how you verified the result. Public repositories or demos are useful where available; do not share confidential material from previous employers.

Ownership, growth & applying

How you will work

• Act as an owner: follow through on agreed deliverables, raise blockers early and communicate progress with concrete evidence.

• Work with the team: collaborate with product and engineering colleagues, accept review constructively and explain technical choices clearly.

• Learn with purpose: pick up unfamiliar tools when the problem requires them, while keeping the solution proportionate to the need.

• Grow through contribution: begin with hands-on individual-contributor responsibility, with potential to take on broader product or team responsibility as delivery, judgement and collaboration develop.

What strong performance looks like

Working features that meet agreed requirements; clear reasoning about implementation; defects investigated systematically; code that others can maintain; and AI-assisted work whose quality you can explain and verify.

Eligibility and compensation

Experience: 1-5 years of hands-on software development experience only.

Freshers are not considered.

Locations: Bengaluru and Belagavi.

Annual CTC : 6-10 LPA

The offer will depend on experience, interview performance and growth potential.

What to expect in the assessment

Be prepared for a discussion of your previous work, a practical coding or debugging task without LLM assistance, and an assessment of how you use AI coding tools and verify their output. We will also discuss product judgement, ownership and collaboration.

Summary

We are looking for an exceptional AI-native full-stack product engineer who can take product specs, prototypes, or PRDs and turn them into clean, tested, QA’d, merge-ready branches.

We are building a fast-moving software company and currently use AI coding tools heavily in our development workflow. Right now, the delivery process is: prototype review, spec clarification, implementation planning, AI-assisted coding, QA, checking what was actually built, and preparing features for final merge.

We want to have this entire workflow managed by the right engineer.

Your job will be to take a feature brief, PRD, prototype, or Loom walkthrough and own the process from:

Input → clarification → implementation plan → AI-assisted build → self-review → QA → PR → merge-ready branch.

We are looking for someone who can take ownership, not create more management work.

What You’ll Do

You will be responsible for:

• Reviewing PRDs, prototypes, tickets, or Loom walkthroughs
• Asking clear, batched clarification questions
• Creating concise implementation plans before coding
• Using AI coding tools to accelerate development
• Reviewing and improving AI-generated code
• Building full-stack product features
• Writing or updating tests where appropriate
• Running QA before handing work over
• Creating clean, reviewable pull requests
• Documenting what was built, what changed, and what risks remain
• Preparing branches that are actually ready to merge
• Communicating clearly and asynchronously

What “Done” Means

A feature is not done when the code is written. A feature is done when:

• The implementation matches the PRD/prototype
• Acceptance criteria are completed
• Code is clean and understandable
• Build/lint/type checks pass
• Relevant tests are added or updated
• Manual QA has been completed
• Screenshots or Loom walkthrough are provided when relevant
• PR description is clear
• Risks, assumptions, and deviations are documented
• The branch is ready for review/merge

Ideal Candidate

You are probably a strong fit if you are:

• An experienced full-stack engineer with strong product judgment
• Experienced with AI coding tools such as Claude Code
• Comfortable taking a vague product idea and turning it into a working feature
• Able to review AI-generated code critically
• Strong with GitHub PR workflows
• Detail-oriented with good QA discipline
• Clear in written communication
• Comfortable working in a fast-moving startup environment
• Able to work independently without needing constant hand-holding
• Good at asking the right questions early

You Are Not a Fit, please do not apply if:

• You blindly trust AI-generated code
• You need every task broken down into tiny instructions
• You say “done” without testing your work
• You create large messy PRs
• You cannot explain your own code
• You are only comfortable with narrow frontend or backend tasks
• You are not comfortable with ambiguity
• You dislike writing implementation plans or QA notes
• You require constant synchronous direction

Required Skills

Please include your experience with:

• Full-stack web development
• Frontend frameworks
• Backend/API development
• Git/GitHub
• Pull request workflow
• Testing and QA
• AI-assisted coding tools
• Debugging and self-review
• Product-focused software development
• Nice to Have
• Startup experience
• Experience as a founding engineer or product engineer
• Strong UX/product taste
• Experience with automated testing
• Experience with CI/CD
• Experience with preview deployments
• Experience turning Figma/prototypes into production features
• Experience working directly with founders

How We Work

We will usually provide one or more of:

• PRD
• Prototype
• Figma
• Loom walkthrough
• Linear/Jira/Notion ticket
• Product brief
• Screenshots
• Existing codebase

You will be expected to return:

• Clarifying questions, if needed
• Implementation plan
• Branch/PR
• QA notes
• Test results
• Screenshots/Loom if relevant
• Clear summary of what was built
• Any risks, tradeoffs, or unresolved questions

Trial Task

We will start with a paid trial task.

The trial will involve a small real feature or product improvement. You will be asked to:

• Review the brief/prototype
• Write a short implementation plan
• Build the feature
• QA it
• Open a clean PR
• Provide a Loom or written walkthrough
• Document assumptions, risks, and anything not completed

We are not just evaluating whether the code works. We are evaluating whether you can own the delivery process end-to-end and how well you leverage AI.

What Success Looks Like

Success means the team can give you a PRD or prototype and receive back a merge-ready branch without needing to manage every step.

Great output looks like:

“I reviewed the feature brief, found two ambiguities, made reasonable assumptions, implemented the core flow, added tests, QA’d happy path and edge cases, documented one tradeoff, and the branch is ready for review. Management's input is only needed on this one product decision.”

Preference will be given to candidates who can work with high ownership and potentially become a long-term product engineering partner.

To Apply, please consider answering the following questions:

• What AI coding tools do you use regularly, and how do you use them?
• Walk us through your process for turning a PRD or prototype into a merge-ready branch.
• How do you QA your own work before asking for review?
• What are the biggest risks of AI-generated code?
• Share an example of a PR, project, or product feature you built that you are proud of.
• What stack are you strongest in?
• Are you comfortable doing a paid trial task?
• What does “merge-ready” mean to you?

About Venxr

VenXR is an AI-driven AdTech startup building AdsGPT, redefining how brands plan, execute, and optimize ad campaigns through AI. We're a fast-growing, lean team looking for a Product Engineer who can own features end-to-end, from idea to shipped product.

About the Role

We're looking for a Product Engineer who thinks like a builder, not just a coder. Someone who cares as much about why we're building something as how it's built, and takes real ownership of the product outcomes, not just the code they ship.

Tech Stack

Frontend: React.js | Backend: Python (Django) | AI: Claude / LLM-driven development

Roles & Responsibilities

• End-to-End Feature Ownership
• Own features from concept to deployment — writing clean, scalable code while staying closely tied to the product goal and user impact behind it.
• Full-Stack Development
• Build and maintain front-end interfaces in React.js and back-end systems in Python/Django, ensuring performance, reliability, and scalability across the product.
• Product Thinking
• Work closely with Product, Design, and Founders to shape specs, question assumptions, and suggest simpler or smarter ways to solve user problems.
• Rapid Iteration
• Ship fast, test in production, gather feedback, and iterate, balancing speed with code quality.
• Cross-Functional Collaboration
• Partner with Design and Data teams to bring dashboards, AI-driven features, and data visualizations to life.
• System Design & Architecture
• Contribute to technical architecture decisions, ensuring the codebase stays scalable as the product and team grow.
• Debugging & Problem Solving
• Diagnose and resolve complex technical issues quickly, treating downtime or bugs as urgent, customer-impacting problems.
• AI-Native Development
• Actively build with AI — using Claude and other LLM tools not just to assist coding, but to develop AI-powered features, prompt workflows, and intelligent product capabilities within AdsGPT itself.

Requirements

• 3–5 years of experience as a Product Engineer, ideally in a startup or B2B SaaS environment
• Strong proficiency in React.js for front-end development
• Strong proficiency in Python, with hands-on experience in Django for back-end development
• Solid understanding of REST APIs, databases (SQL/NoSQL), and system design fundamentals
• Hands-on experience building with AI tools (like Claude), not just using them for coding assistance, but developing core AI products.
• Experience working directly with Product/Design teams, not just executing tickets
• Comfortable working in ambiguous, fast-changing environments with minimal hand-holding
• Strong debugging and problem-solving skills

Good to Have

• Familiarity with the Model Context Protocol (MCP) for securely connecting LLMs to external tools and APIs.
• Experience building conversational AI interfaces or managing complex multi-turn chatbot state across various platforms and channels.
• Experience in AdTech, MarTech, or data-heavy SaaS platforms.
• Exposure to cloud infra (AWS/GCP/Azure), Docker, and CI/CD pipelines.
• Experience with LLM evaluation/monitoring tools (Ragas, LangSmith, Langfuse, or similar).
• Experience with data visualization libraries (Recharts, D3.js, Chart.js).
• Familiarity with compliance-aware or explainable AI design in regulated domains.

What We Look For In Candidates

• Customer Obsession – A genuine curiosity about how your code impacts the customer's experience, not just whether it compiles.
• Ownership – You drive features to completion, chasing down blockers instead of waiting on them.
• Stakeholder Understanding & Management – You know when to loop in Product, Design, or Business to unblock yourself fast.
• High Standards – You hold your own code to a higher bar, even when no one's checking.
• Disagree and Commit – You debate technical decisions hard, then commit fully once the call is made.
• Simplify Relentlessly – You reach for the simplest working solution, not the most "clever" one.
• Solidarity with the Team – You show up for your teammates, no invitation needed.
• Vitality – You bring real energy and resilience that keeps you (and others) going.

• Why Join Venxr?
• Be part of a fast-growing startup that puts data at the heart of every decision.
• Opportunity to work on high-impact, real-world business challenges.
• Collaborative, transparent, and learning-oriented work environment.
• Flexible work culture with a strong focus on career development.
• Comprehensive health benefits to support your well-being.
• Team offsites and engagement activities to build stronger connections beyond work.
• Performance-based incentives and rewards recognizing your contribution and impact.

We are looking for an Engineering Lead to own the entire technology stack — from onboarding and underwriting to disbursals, repayments, and collections — and to build the engineering function into something genuinely AI-native. 

What You'll Own 

● Full tech stack: backend, frontend, infrastructure, integrations, and data pipelines 

● Real-time underwriting and decisioning systems 

● LOS/LMS architecture — onboarding, disbursals, repayments, and collections

● Integrations with bureaus, KYC providers, account aggregators, and payment gateways 

● Reconciliation systems — disbursement, repayment, and NACH reconciliation end-to-end 

● AWS infrastructure: scaling, reliability, uptime, and cloud cost ownership ● Data infrastructure for the credit and risk team — feature pipelines, model serving, experiment infrastructure 

● Engineering leadership: hiring, sprint planning, code reviews, and execution standards 

● Compliance systems: RBI guidelines, DPDP, KYC/AML, e-NACH, e-sign 

AI-Native Engineering 

This is a core part of the role, not a bonus. You will build a machine-readable knowledge base of the entire codebase — architecture, data models, service contracts, coding standards, decision history — so that AI agents working on code have the context to produce accurate, consistent output. You will build skills for code review, developer onboarding, and recurring engineering workflows. You will build a code review pipeline where agents do the first pass on every pull request. The knowledge base and the skills improve over time as the team grows and the product evolves. 

What We're Looking For 

● 7+ years in software engineering, with at least 2 years leading teams or architecture

● Strong hands-on experience with Python, Django, and React Native

● Deep expertise in AWS and cloud-native architecture 

● Experience with both SQL and NoSQL databases 

● Strong understanding of distributed systems, microservices, and API design

● Experience owning reconciliation or payment flow infrastructure in a lending or payments context

● Prior experience in fintech / NBFC / digital lending — mandatory

● Strong understanding of the full loan lifecycle — mandatory 

● You have used LLMs seriously as engineering tools and have strong opinions about what makes AI-assisted development produce good output versus mediocre output 

Bonus: Kubernetes / Kafka, AI/ML-driven underwriting, Account Aggregator framework, e-NACH / e-Sign / Video KYC integrations 

What Success Looks Like 

● scales with strong uptime, performance, and reliability

● Reconciliation runs cleanly — no financial discrepancies surface late ● A new engineer joins and is writing standard, correct code within their first week

● The credit team is never blocked on an engineering dependency 

● Engineering health metrics are tracked and visibly improving 

● AI agents are doing the structured first pass on code reviews, and the system gets smarter over time 

Location : Mumbai

Big Picture (The Opportunity) :

Are you looking for an opportunity to advance your Career? & If you are able to maintain a positive attitude even when everything goes wrong, if you are detail oriented and self motivated with a passion to learn and improve your skills and knowledge, we have a perfect job for you !

What do we want from you ? (Our Expectations) :

• Zero to 2 years experience in Linux Operating System.
• Flexible working hours - able to support occasional nights, weekends, and call-ins, able to quickly adapt to a constantly changing faced paced environment. Open to travel to sites.
• An ideal person who is excited and motivated about running and supporting a production - grade critical infrastructure and looks for opportunities to improve processes with automation.

What are you required to do ? (Your Responsibilities) :

• Proactively maintain and develop all linux infrastructure technology to maintain a 24*7*365 uptime service.
• Engineering of systems administration-related various solutions for our various SAAS products and projects as well as operational needs.
• Proactively monitoring system performance and capacity planning.
• Providing technical support to customers for Applications, Operating systems, and networking.
• Will also be the first point of contact for our clients, where installations are placed on a permanent basis, for basic troubleshooting and problem solving.
• Fault finding, analysis and logging information for reporting of performance exceptions.
• Maintain best practices on managing systems and services across all environments.

Skills & Qualification Required (Add Value) :

• Graduate - Preferred to have Bachelor‘s Degree in Engineering, Computer Science or related field.
• He / She should be familiar with the installation and configuration of Linux operating systems and setup and operation of TCP/IP networking on Linux systems also familiar with Internet concepts including SMTP, IMAP, POP, HTTP, DNS, LDAP and related protocols.
• You should possess excellent communication skills .
• Knowledge of Email concepts, Helpdesk Concept , VoIP Concept , Cloud computing will be an added advantage.

About the Role

Pendo is looking for a Staff Software Engineer to lead teams building core product capabilities across Analytics, Guides, and Platform services. These are the systems that power how hundreds of millions of end users experience the software.

In this role, you will drive execution against business objectives, direct complex initiatives from kickoff through delivery, and build a team that operates with clarity and focus. You will set clear expectations, delegate effectively, and partner closely with product, design, and senior engineering leadership to keep teams aligned and moving. You default toward action, push teams to deliver value daily, and actively use AI tools as part of how you work.

If you're energized by directing high-impact teams, developing strong engineers, and building a culture where craft and velocity coexist, this role is a great fit.

What You'll Do

Team Leadership & Hiring

• Create an environment where engineers are encouraged to take risks, experiment, and challenge the status quo.
• Lead, mentor, and grow a team of engineers through clear expectations, coaching, and timely feedback.
• Own hiring end-to-end, partnering with recruiting to attract and close top engineering talent.
• Build an inclusive, high-performing team culture grounded in ownership, accountability, and continuous improvement.

Delivery & Execution

• Maintain a high bar for velocity, predictability, and quality.
• Own team execution against product and engineering goals.
• Partner with Product and Design to define roadmaps, scope work, and deliver high-quality outcomes.
• Identify and remove blockers, manage risks, and ensure strong planning and prioritization.

Cross-Functional Collaboration

• Work closely with product, design, infrastructure, and other engineering teams to deliver cohesive customer experiences.
• Align team priorities with broader organizational goals and strategy.

Operational Excellence

• Drive improvements in system reliability, performance, and scalability.
• Establish strong practices around monitoring, incident response, and continuous improvement.

What We're Looking For

• 8+ years of experience in software engineering.
• 3+ years of experience managing and growing engineering teams.
• Proven track record of hiring and building high-performing teams.
• Experience delivering complex, cross-functional initiatives in a product-driven environment.
• Strong technical foundation in backend, distributed systems, or full-stack development.
• Proven ability to lead teams through ambiguity and change while maintaining execution.
• Actively uses AI tools in day-to-day work and helps drive adoption across teams.
• Strong communication, organizational, and stakeholder management skills.

Nice to Have

• Experience working on analytics products, user-facing SaaS platforms, or data-intensive systems.
• Experience managing teams across both frontend and backend domains.
• Familiarity with modern cloud environments and scalable architectures.
• Experience working in distributed teams across multiple time zones.