Forward Deployed Engineer (FDE)

About the Role:

We are looking for a Forward Deployed Engineer to work closely with customers and build technical solutions to solve real-world business problems.

This is a highly customer-facing engineering role, combining full-stack development, AI and solution engineering. You will work in ambiguous environments, take end-to-end ownership and turn customer requirements into working product solutions.

Key Responsibilities:

• Work directly with customers to understand technical and business requirements.
• Design, build and deploy full-stack solutions and product features.
• Integrate AI/LLM capabilities into applications and workflows.
• Troubleshoot technical challenges and develop practical solutions.
• Collaborate with product and engineering teams to deliver customer-focused solutions.
• Take ownership of projects from requirement gathering through implementation.
• Work effectively in fast-paced and ambiguous environments.

What We're Looking For:

• Experience as a Full Stack Engineer, Product Engineer, AI Engineer, Solutions Engineer, Solutions Architect or similar role.
• Strong understanding of both frontend and backend development.
• Experience building and contributing to real-world product features.
• Exposure to AI/LLMs, Copilots, AI automation or GenAI tools.
• Strong problem-solving and customer-facing communication skills.
• Ability to work independently and take ownership of outcomes.
• Comfortable working with evolving requirements and ambiguity.

Preferred Background

• Candidates from product/SaaS companies, AI startups, or modern technology environments are preferred.
• Experience working with product clients through a service-based organization will also be considered, provided you have strong hands-on product engineering experience.
• Important: This is not a backend-only role. Strong full-stack exposure and the ability to work directly with customers are essential.

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

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

• 1-2 years of experience as a Product Engineer, ideally in a startup or B2B SaaS environment
• Candidates with B.Tech in CSE, AI/ML or any other equivalent educational background from Tier-1 and Tier-2 colleges will be preferred
• 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.

• 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 or 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.

What You Bring

• Bachelor’s degree in computer science, Software Engineering, or related field with 7+ years of relevant professional experience.
• Deep production experience with Python and JavaScript/TypeScript across backend and frontend, with demonstrated ability to work comfortably across the full stack.
• Strong experience with modern frontend frameworks (such as Next.js or React) and backend API development.
• Extensive experience with cloud platforms (AWS preferred; Azure or GCP also valued), including infrastructure-as-code tools (such as CloudFormation or Terraform).
• Deep Working knowledge of multiple database paradigms, including relational databases (such as PostgreSQL), document databases, and key-value stores (such as Redis), with the ability to select the right storage technology for each problem.
• Strong experience with CI/CD pipelines (such as GitHub Actions), containerisation, and production deployment strategies.
• Demonstrable fluency with AI coding tools (such as Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on AI-augmented development practices.
• Hands-on experience architecting production generative AI applications (LLM integrations, vector databases, RAG systems, evaluation pipelines) is essential.
• Experience leading technical initiatives across multiple teams, mentoring engineers, and establishing engineering practices is required.
• Experience navigating ambiguous problem spaces, working directly with business stakeholders and end users, and shipping working solutions rapidly is required.
• Experience in an embedded, forward-deployed, or consulting-style engineering model is a strong plus.

• Must have exceptional communication skills and demonstrated ability to influence at senior levels. This role requires comfort leading across ambiguous environments, building trust-based relationships with commercial stakeholders at all levels, developing junior and mid-level engineers, and making strategic decisions that balance delivery speed with architectural integrity. You will shape engineering practices across your area and be expected to lead multi-team initiatives.

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.

About Dino Ventures

Dino Ventures is a Bharat-focused, app-first technology company with 5M+ app downloads across a portfolio of 10+ live applications. Our flagship products—including Samaj Saathi, Samjho, and Stick—serve millions of users across India, solving meaningful problems at scale.

We’re building products that impact everyday lives, and we’re looking for experienced engineers who thrive on ownership, performance, and shipping high-quality software.

What You’ll Do

• Architect, build, and scale high-performance, real-time applications across the entire stack.
• Design robust backend services, APIs, and distributed systems that power millions of users.
• Build fast, responsive, and polished user experiences with a strong focus on performance and usability.
• Optimize databases, caching layers, and application architecture for scalability, reliability, and cost efficiency.
• Lead technical design discussions, make architectural decisions, and mentor fellow engineers.
• Drive projects from concept to production with complete ownership.
• Collaborate closely with product and design teams to build impactful user experiences.
• Leverage modern AI-assisted development tools (Claude Code, Codex, Cursor, etc.) to maximize engineering productivity.

Our Tech Stack

Backend

• Node.js
• TypeScript
• PostgreSQL
• Redis
• Elasticsearch

Frontend

• SvelteKit
• TypeScript
• Tailwind CSS
• tRPC
• TanStack Query

(We’re pragmatic about technology—we choose the right tool for the job.)

What We’re Looking For

• 2+ years of experience building and shipping production-grade software.
• Strong expertise in TypeScript/JavaScript across frontend and backend development.
• Deep understanding of software engineering fundamentals, system design, and scalable architecture.
• Strong knowledge of relational databases, indexing strategies, query optimization, and database internals.
• Experience building scalable REST APIs and real-time systems.
• Familiarity with caching, asynchronous processing, networking, and distributed systems.
• Experience using modern AI coding tools to accelerate development workflows.
• Strong attention to engineering quality, including latency, reliability, race conditions, bundle size, and user experience.
• Ability to balance speed with maintainability, making thoughtful engineering trade-offs.
• Self-driven with a strong sense of ownership and a product mindset.

Intent > Experience > Skills

Why Join Dino Ventures?

• Build products that solve real problems for millions of Bharat users.
• Work across multiple products with opportunities to build new systems from scratch.
• High ownership, minimal bureaucracy, and fast decision-making.
• Collaborate with an ambitious, product-first engineering team.
• See your work reach production from Day 1.
• Shape the technical direction of products used at massive scale.

If you enjoy solving challenging engineering problems, care deeply about software craftsmanship, and want your work to make a real-world impact, we’d love to hear from you.

Full-Stack Engineer (AI-Native) | 2-4 Years Experience

About the Role

We're hiring a Full-Stack Engineer who is equally comfortable building a polished Next.js interface and a reliable NestJS API behind it. You'll build customer-facing products, including AI-powered features like chat interfaces, streaming responses, and agent-driven workflows. You'll own features end to end, from database schema to UI, and use AI tools daily to ship faster without lowering the quality bar.

What You'll Do

Frontend

• Build responsive, accessible, high-performance UIs with React, Next.js (App Router, RSC) and TypeScript
• Build AI-facing interfaces: streaming chat UIs, tool-call/agent-status displays, and loading, error, and retry states for non-deterministic outputs
• Monitor web vitals and fix performance regressions

Backend

• Design and build scalable REST/GraphQL APIs and services with Node.js and NestJS
• Model, query, and optimize data in PostgreSQL (schema design, indexing, migrations) using an ORM like Prisma or Drizzle
• Implement auth, authorization, validation, background jobs, queues, and caching (Redis)
• Integrate LLM APIs (OpenAI, Anthropic, Gemini), including streaming (SSE/WebSockets), tool calling, retries, rate limits, and cost/latency control

AI-Assisted Engineering

• Use AI coding tools (Cursor, Claude Code, Copilot, etc.) for scaffolding, refactoring, debugging, and test writing
• Write and maintain project context for AI tools (rules files, AGENTS.md/CLAUDE.md, reusable prompts) so the whole team gets better output
• Review AI-generated code critically for correctness, security, performance, and maintainability

Team and Delivery

• Write unit, integration, and E2E tests, using AI to speed them up rather than skip them
• Take part in code reviews, sprint planning, architecture discussions, and on-call/incident follow-ups
• Document APIs, decisions, and runbooks clearly

Must-Have (Non-Negotiable)

Frontend

• Strong JavaScript (ES6+) and TypeScript
• React (hooks, state management, rendering behavior) and Next.js (App Router, SSR/SSG/RSC)
• HTML/CSS fundamentals, Tailwind or similar, responsive design, and accessibility basics

Backend

• Production experience with Node.js and a structured framework (NestJS preferred; Express/Fastify with good architecture is fine)
• Solid PostgreSQL skills: relational modeling, joins, indexes, transactions, query optimization
• API design: REST principles, pagination, versioning, error handling, input validation
• Authentication and authorization (JWT, OAuth2, sessions, RBAC)

Engineering Fundamentals

• Git, PR workflows, and code review habits
• Testing across layers (Jest/Vitest, React Testing Library, API/integration tests; Playwright/Cypress is a plus)
• Basic security awareness (OWASP top 10, secrets management, input sanitization)

AI-Assisted Development

• Daily, hands-on use of at least one AI coding tool (Cursor, Claude Code, Copilot, Windsurf, or similar)
• Ability to write clear prompts, give useful context, and break big tasks into steps an AI can handle
• Habit of reviewing, testing, and understanding AI output before committing it
• Basic understanding of how LLMs work: context windows, hallucinations, token cost, and why outputs vary

Nice to Have

• Redis, message queues (BullMQ, SQS, Kafka), or event-driven architecture
• Monorepo tooling (Turborepo, pnpm workspaces, Nx)
• Design system or component library work (shadcn/ui, Radix, Storybook)
• tRPC, GraphQL, or OpenAPI-driven type-safe clients
• Multi-tenant SaaS, payments (Stripe/Razorpay), or real-time features
• Open-source contributions, a side project, or shipped AI features you can demo

What We Expect From You

• Ownership: take a feature from schema to UI to production, and flag risks early
• Judgment over speed: AI makes you faster, and you're still accountable for every line you ship
• Security awareness: no secrets in prompts, no blind copy-paste of AI code, and sensitive data stays out of third-party tools
• Systems thinking: consider scale, failure modes, and cost, not just the happy path
• Learning speed: the AI tooling landscape changes every few months, and you keep up and share what works
• Clear communication: PRs, docs, and async updates that others can follow

If interested for this job pls contact us on this WhatsApp number, nine three one six one two zero one three two

Position Overview

We are seeking a versatile Senior Full Stack & AI Agent Developer to architect, build, and

maintain end-to-end software solutions spanning web platforms, desktop applications, and

autonomous AI agents capable of interacting with and controlling these software systems.

The ideal candidate will bridge traditional engineering software with cutting-edge artificial

intelligence to automate data processing and enhance operational decision-making. While

not strictly required, a background or strong interest in the energy sector—specifically

drilling and completion operations—is highly desirable.

Key Responsibilities

• Full Stack Development: Design, develop, and deploy robust web applications and

native desktop software utilized by engineering and operational teams.

• AI Agent Engineering: Build, train, and integrate autonomous AI agents and LLM-

driven workflows capable of interpreting data, executing commands, and safely

controlling desktop and web-based software.

• Workflow Automation: Translate complex workflows into intuitive software features

and autonomous agent actions, minimizing manual data entry and operational

bottlenecks.

• Data Integration: Handle high-frequency data streams and integrate them seamlessly

into user interfaces and backend AI models.

• Architecture & Scalability: Ensure high performance, security, and scalability across

cloud infrastructure (AWS/Azure), local desktop environments, and potential edge

computing setups.

• Cross-Functional Collaboration: Work closely with domain experts and end-users to

translate field challenges into technical product requirements.

Required Qualifications & Experience

• Experience: Minimum of 5 years of professional software development experience,

with a proven track record of delivering production-ready web and desktop

applications.

• Programming Languages: Strong proficiency in Python, JavaScript/TypeScript, and at

least one compiled language (C#, C++, or Java).• Web & Desktop Frameworks: Hands-on experience with modern frontend

frameworks (React, Angular, or Vue.js), Node.js, and desktop application development

(Electron, WPF, Qt, or Tauri).

• AI & Agent Tooling: Demonstrated experience building AI agents using LLM APIs

(OpenAI, Anthropic), open-source models (Hugging Face), LangChain, LlamaIndex,

AutoGPT, or custom agent architectures.

• Automation & UI Control: Expertise in software control mechanisms using tools like

Selenium, Playwright, PyAutoGUI, Appium, or computer vision-based GUI automation to

allow AI agents to navigate software.

• Cloud, DevOps & Databases: Experience with Git, Docker, CI/CD pipelines, cloud

platforms (AWS/Azure/GCP), RESTful APIs, GraphQL, and relational/NoSQL databases.

Preferred Qualifications (Strong Plus)

• Industry Domain Expertise: Prior hands-on development experience within the oil and

gas sector, specifically focused on drilling, completions, rig operations, or subsurface

engineering software.

• Data & Protocols: Familiarity with oilfield data standards (e.g., WITSML, OPC-UA) and

time-series databases.

• Experience deploying AI models and agents in edge or low-connectivity environments

(such as offshore rigs or remote drilling sites).

• Familiarity with safety-critical software design and cybersecurity standards in

industrial control systems (ICS/SCADA).

• Degree in Computer Science, Software Engineering, Petroleum Engineering, or a related technical discipline.

The role

A working product and a working deployment are two different things. You are the person who closes that gap.

You sit inside the client's head office. You get the deployment live, you get their teams using the dashboards, and you own whether the AI is returning something worth acting on. Every client is different: different languages on the floor, different store noise, different vocabulary for the same product, different CRM, different idea of what a good conversation looks like. The core platform does not change for each of them. You are the layer that makes it fit, and you are the one the client meets.

You are encouraged to spend time in stores. The engineers who do the best work here are the ones who have stood on a shop floor and watched where the pitch and the pipeline actually break. Nobody will make you go. You will also spend real time in the codebase, because you fix what you find rather than filing it.

What you build has a commercial edge to it. A pilot converts when the client sees the result they were promised, and an account grows when a second team inside it sees what is already sitting in their data. Both of those outcomes are yours to deliver, not somebody else's to chase.

How you will work

You design the deployment, you build it, and you own whether it holds up on a Saturday evening in a crowded store. Nobody hands you the plan, and nobody hands you the spec. You write both.

The decisions are yours. Which integration is worth the week, which vertical taxonomy needs building, what ships in the pilot and what waits, and when to tell a client that the thing they are asking for is the wrong thing to build. You go and find out what a client needs before anyone writes a line of code.

You will not be doing it alone. There are founders, AI engineers and product people around you, and they will build alongside you. What nobody will do is tell you what the client needs. That call is yours.

The work compounds if you do it well. What you learn on one deployment becomes a specification, then code, then a pattern the next one starts from. A year in, the deployments you designed should be running without you, and a new client should take a fraction of the time the first one did.

What you will do

Own the deployment end to end. Device provisioning, store connectivity, data flowing, first insight in front of the client. Get from kickoff to something real inside

the pilot window, and know by the halfway mark whether it is in trouble.

Get their HQ using it. A dashboard nobody opens is a failed deployment. Sit with the sales, marketing and L&D teams, show them what is in their own data, and

make sure the people who asked for this are actually looking at it every week.

Make the AI work on their floor. Their languages, their store noise, their product vocabulary. Benchmark transcription and speaker separation on their actual

audio, and fix what fails instead of explaining it away.

Build the vertical. Intent taxonomies, objection maps and prompt libraries for the category you are deployed into. A jewellery floor and an electronics floor do not

share a conversation model.

Wire it into their systems. CRM and POS integrations, so conversation data connects to what actually got sold and the insight can be checked against reality.

Build what the client asks for. Custom reports, dashboards and agents. Ground everything in source conversations and verify it before it ships, because a confident

wrong number costs an account.

Close the pilot. A pilot converts on results, not on effort. Know what the client agreed to judge this on, work backwards from it, and make sure the output in front of

their leadership at the end is the thing they asked for.

Grow the account. The same intelligence is worth something to marketing, L&D and category teams inside the same client. Spot which of them would benefit, show them what is already in their data, and hand a real opening to the account team.

Push it back into the product. Turn one-off client work into something the platform does by default, so the next deployment starts further ahead than this one did.

What we are looking for

Must have

• 0 to 5 years of experience. A consulting internship or an analyst role is the closest match to what this job actually asks for, but we care more about what you can do than where you did it
• Coding ability, ideally Python. Degree, internship, first job or your own projects. What we want to see is something you built that other people actually used
• Excel or Sheets at a real working level. A lot of the first conversation with a client happens in a spreadsheet before it ever happens in a dashboard
• The ability to explain a complicated idea simply. You will be taking AI output to people who do not think about models, and the explanation matters as much as the result
• Comfort at the boundaries. APIs, data pipelines, some frontend, some hardware when a device misbehaves
• An eye for where a deployment turns into more business, and the willingness to raise it yourself
• Heavy hands-on LLM usage. Prompts, evaluations, retrieval, and a clear view on where these tools break
• Fluent English and Hindi. A third Indian language counts for a lot, since the useful conversations happen on store floors and not only in HQ meeting rooms
• The instinct to go and find out what a client needs rather than waiting to be told

Good to have

Speech or audio work. Transcription, diarization, voice activity detection, or

anything that survives noisy real-world recording

Embedded or IoT experience, on ESP32 or similar

SQL and experience building things customers actually look at

Side projects, hackathons or internships where you shipped without a spec

and it worked

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