Department : AI Solutioning

Experience : 3 - 5 Years

Employment Type : Full-Time

Location : Bangalore / Chennai, India (Hybrid)

Reports To : Lead - AI Solutions

About Flatworld Solutions :

Flatworld Solutions is a leading IT and business services company delivering end-to-end technology solutions across software development, data management, AI/ML, and digital transformation. Our AI Solutioning team turns enterprise problems into working software - fast.

Role Summary :

We are hiring an Associate Full Stack Engineer to be the builder inside our AI Solutioning team. Your job is to turn ideas into working software quickly - spinning up prototypes across multiple concepts each quarter, then taking one or two of the most promising ones to a deployable, demo-ready MVP that powers client pitches. This is a build-fast, iterate-often role. You will own the full stack - frontend, backend, database, and deployment - with the AI Solutions Lead handling client presentation and business framing. If you enjoy shipping something new every few weeks over maintaining the same codebase for years, this role will suit you.

Key Responsibilities :

A. Rapid Prototyping :

- Build functional prototypes for multiple solution concepts in parallel - typically 2 to 4 week build cycles per idea.

- Translate solution blueprints and wireframes from the AI Solutioning team into working, clickable applications.

- Make pragmatic technical trade-offs : choose speed-to-demo over premature optimisation, while keeping the code clean enough to extend.

- Rapidly evaluate and integrate third-party APIs, SDKs, and open-source components to avoid building from scratch.

B. MVP Development & Deployment :

- Take one or two selected prototypes per cycle to production-grade MVP : authentication, data persistence, error handling, and responsive UI.

- Own end-to-end deployment - containerise, configure environments, and deploy to cloud platforms (AWS, Azure, GCP).

- Set up and maintain CI/CD pipelines so every MVP has a repeatable, one-command deploy path.

- Ensure MVPs are demo-stable : seeded data, reliable uptime during pitch windows, and failure handling.

- Instrument basic logging and monitoring so issues surfacing during a client demo can be diagnosed quickly.

C. Client-Pitch Enablement (Build Support) :

- Prepare demo environments and walkthrough-ready builds ahead of client pitches; the AI Solutions Lead presents; you make sure it works.

- Produce short technical notes and architecture diagrams the Lead can use to answer client questions during pitches.

- Turn client feedback captured in pitch sessions into prioritised build tickets and rapid iterations.

- Maintain a reusable component and boilerplate library so each new prototype starts further along.

D. Engineering Practice & Collaboration :

- Maintain disciplined version control : feature branching, meaningful commit history, pull requests, and code review participation.

- Write concise technical documentation - setup instructions, environment variables, API contracts, and deployment runbooks.

- Collaborate closely with business analysts, designers, and the AI Solutions Lead in short, iterative cycles.

- Contribute to internal accelerators and shared tooling that shorten the path from idea to demo.

Mandatory Technical Requirements :

- JavaScript / TypeScript : Strong proficiency with modern JS/TS. Hands-on production experience with React and at least one of Next.js or Express.js.

- Databases : Working experience with MongoDB and PostgreSQL - schema design, indexing, query optimisation, and migrations.

- Application Deployment : Demonstrated experience deploying and running applications in a live environment - containerisation (Docker), environment configuration, and cloud or PaaS deployment.

- Version Control : Proficiency with Git and GitHub (or GitLab / Bitbucket) - branching strategies, pull requests, merge conflict resolution, and CI/CD integration.

- REST API Development : Ability to design, build, document, and secure RESTful APIs.

Strongly Preferred :

- Vector Databases : Hands-on experience with Pinecone, Qdrant, Chroma, or pgvector.

- Frontend Depth : Tailwind CSS, state management (Redux Toolkit, or React Query), and component-driven development.

- Backend Patterns : Asynchronous processing, job queues, caching (Redis), and webhook handling.

- Cloud Services : Familiarity with AWS (EC2, S3, Lambda), Azure, or GCP core services.

Advantageous (ML / AI Exposure) :

- Working knowledge of LLM APIs (OpenAI, Anthropic, Google) - prompt construction, streaming responses, token and cost management.

- Experience building RAG pipelines : document chunking, embedding generation, and retrieval-augmented response flows.

- Familiarity with orchestration frameworks such as LangChain, LlamaIndex, or agentic patterns.

- Exposure to Python for ML workflows, or integrating Python ML services into a Node.js application.

- Understanding of core ML concepts : model evaluation, embeddings, fine-tuning trade-offs, and inference cost.

What We Look For (Beyond the Stack) :

- Bias toward shipping - you would rather have something working and imperfect than perfect and unbuilt.

- Comfort with ambiguity : specifications will sometimes be a wireframe and a conversation.

- Breadth over narrow specialisation; genuine curiosity about unfamiliar tools.

- Ability to estimate honestly and flag scope risk early rather than late.

- A public portfolio, GitHub profile, or side projects that show what you build when nobody assigns it.

Qualifications :

- Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent practical experience.

- 3 - 5 years of hands-on full stack development experience with at least one application taken from zero to live deployment.

- Prior experience in a startup, product studio, innovation lab, or fast-paced consulting environment is a plus.

What We Offer :

- Variety - you will build across multiple domains and problem spaces rather than one product forever.

- Direct line of sight from your code to a real client decision.

- Freedom to pick the right tools for each prototype, within sensible guardrails.

- Mentorship from the AI Solutions Lead and exposure to enterprise solutioning practice.

- Learning budget for AI/ML upskilling and cloud certifications.

- Competitive compensation with a clear path toward Senior Engineer or Solution Engineer tracks.

The job is for:

May work from home