Flatworld - AI/ML Engineer - LLM/RAG (India)

Flatworld - AI/ML Engineer - LLM/RAG (India)

01 Oct
|
Hirist.tech
|
India

01 Oct

Hirist.tech

India

Note : If screened-in, you will be invited for initial rounds on 10th October 2026 (Saturday) in Bangalore.

Position Title : AI/ML Engineer

Department : AI Solutioning

Experience : 4 - 7 Years

Employment Type : Full-Time

Location : Bangalore

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 AI systems - fast.

Role Summary :

We are hiring an AI/ML Engineer to build the intelligence layer inside our AI Solutioning team. You will design and ship the AI components behind our prototypes and client MVPs - LLM integrations, retrieval-augmented generation (RAG) pipelines, agentic workflows, conversational and voice AI, and classical ML models where they are the better fit.

Key Responsibilities :

A. LLM & Generative AI Solution Build :

- Design and build LLM-powered components - RAG pipelines, document intelligence, summarisation, classification, extraction, and conversational agents.
- Develop agentic workflows using tool calling, multi-step orchestration, and explicit guardrails.
- Engineer prompts, system instructions, and structured output schemas.
- Select the right model for each task across commercial APIs and open-weight models.

B. Data, Retrieval & Model Development :

- Build ingestion pipelines for client data : document parsing, chunking, embedding generation, and metadata enrichment.
- Design and tune retrieval - vector search, hybrid search, re-ranking, and query rewriting.
- Build, train, and evaluate classical ML models where the problem calls for them.

C. Evaluation, Quality & Cost Control :





- Build evaluation harnesses : golden datasets, automated metrics, LLM-as-judge scoring, and human review loops.
- Measure and reduce hallucinations, retrieval misses, and edge-case failures.
- Track token usage, latency, and cost per transaction.

D. Deployment, MLOps & Collaboration :

- Package AI services as clean APIs (FastAPI or equivalent).
- Containerise and deploy AI services to cloud platforms (AWS, Azure, GCP).
- Support the AI Solutions Lead in pre-sales and architecture notes.

Mandatory Technical Requirements :

- Python : Strong production-grade Python.
- LLM Application Development : Hands-on experience building on LLM APIs (Anthropic, OpenAI, Google, or Azure OpenAI).
- RAG & Vector Databases : End-to-end RAG system experience (Pinecone, Qdrant, Chroma, pgvector, or similar).
- ML Fundamentals : Supervised learning, evaluation metrics, scikit-learn, and PyTorch or TensorFlow.
- AI Evaluation : Demonstrated practice of measuring AI output quality.
- API Development & Deployment : REST APIs, Docker, cloud deployment, and Git.

Qualifications :

- Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, Statistics, Engineering, or equivalent.
- 4 - 7 years of hands-on experience in ML or software engineering, including at least 2 years building LLM or Generative AI applications.
- At least one AI solution taken from prototype to live deployment.

What We Offer :

- Variety of industries and AI use cases.
- Direct line of sight from your models to a real client decision.
- Access to current commercial and open-weight models.
- Mentorship and exposure to enterprise solutioning.
- Learning budget for AI/ML upskilling.
- Competitive compensation with a clear path toward Senior AI Engineer or AI Solution Architect tracks.

📌 Flatworld - AI/ML Engineer - LLM/RAG (India)
🏢 Hirist.tech
📍 India

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