AI Engineer · Mid–Senior

Think Right Advisory Services Pvt. Ltd.; Anekal; Hybrid; INR 2,500,000 - 4,000,000; Full time

Job summary

Think Right Advisory Services Pvt. Ltd. is seeking an AI Engineer to build and ship in-product AI features such as copilots, semantic search, and rule-suggestion engines.

You will work on end-to-end pipelines from prompt design to deployment in production. The role demands 5+ years software engineering experience with 3+ years shipping LLMs, strong Python, and hands-on with LangChain, LlamaIndex, and major APIs.

Qualifications

• 5+ years software engineering experience with 3+ years shipping LLMs in production.
• Strong Python with async APIs and data pipelines.
• Hands-on with LangChain, LlamaIndex or equivalent orchestration frameworks.
• Experience with OpenAI/Anthropic/Gemini APIs including function calling and structured outputs.
• Familiarity with embedding models and vector databases (Pinecone, pgvector, Qdrant).
• Solid NLP fundamentals: tokenization, NER, relation extraction and summarisation.
• Experience shipping AI features end-to-end from prototype to production.

Responsibilities

• 01 Implement, evaluate and ship LLM features end-to-end — RAG, tool-use, agents and fine-tunes
• 02 Design and iterate on prompt strategies: chain-of-thought, few-shot, structured outputs, function calling
• 03 Build the in-product AI copilot — answering steward questions, suggesting rules and explaining match decisions
• 04 Develop evaluation harnesses with telemetry, guardrails and offline + online evals
• 05 Integrate and benchmark third-party APIs (OpenAI, Anthropic, Gemini, AWS Bedrock) for cost and latency
• 06 Collaborate with the ML Engineer on embedding strategies, retrieval quality and rerankers
• 07 Work with backend engineers to package AI components as well-defined, observable microservices
• 08 Maintain prompt and model version control with rollback capability for production AI features
• 09 Document system behaviour, failure modes and known limitations for every shipped AI feature

Skills

Python

Async APIs

LLMs in production

NLP fundamentals

End-to-end shipping

Evaluation

Data pipelines

Tools

LangChain

LlamaIndex

OpenAI

Anthropic

Gemini

AWS Bedrock

Pinecone

pgvector

Qdrant

Python (async)

FastAPI

BLEU

ROUGE

BERTScore

LoRA

QLoRA

PEFT

Job description

Position

AI Engineer

Location

Bangalore, IN

BHIVE Workspace, AKR Tech Park (Kudlu Gate)

Employment

Full-time

Hybrid 5+ years (3+ years shipping LLMs in production)

Role Summary

Build and ship the applied AI layer — the in-product copilot, semantic search, rule-suggestion engine and structured-output features that customers use every day.

Key Technologies

LLM Features RAG Prompt Engineering Eval Harnesses Python

Team

AI / Applied

Experience

5+ years (3+ years shipping LLMs in production)

Tech Stack

• LangChain
• LlamaIndex
• OpenAI
• Anthropic
• Gemini
• AWS Bedrock
• Pinecone
• pgvector
• Qdrant
• Python (async)
• FastAPI
• BLEU
• ROUGE
• BERTScore
• LoRA
• QLoRA
• PEFT

What you’ll do

• 01 Implement, evaluate and ship LLM features end-to-end — RAG, tool-use, agents and fine-tunes
• 02 Design and iterate on prompt strategies: chain-of-thought, few-shot, structured outputs, function calling
• 03 Build the in-product AI copilot — answering steward questions, suggesting rules and explaining match decisions
• 04 Develop evaluation harnesses with telemetry, guardrails and offline + online evals
• 05 Integrate and benchmark third-party APIs (OpenAI, Anthropic, Gemini, AWS Bedrock) for cost and latency
• 06 Collaborate with the ML Engineer on embedding strategies, retrieval quality and rerankers
• 07 Work with backend engineers to package AI components as well-defined, observable microservices
• 08 Maintain prompt and model version control with rollback capability for production AI features
• 09 Document system behaviour, failure modes and known limitations for every shipped AI feature

What we’re looking for

• 5+ years software engineering experience; 3+ years working directly with LLMs in production
• Strong Python — async APIs, data pipelines and clean, testable code
• Hands-on with LangChain, LlamaIndex or equivalent orchestration frameworks
• Experience with OpenAI / Anthropic / Gemini APIs including function calling and structured outputs
• Working knowledge of embedding models and vector databases (Pinecone, pgvector, Qdrant)
• Strong NLP fundamentals: tokenization, NER, relation extraction and summarisation
• Solid grasp of evaluation methodology — BLEU/ROUGE/BERTScore plus task-specific evals
• Experience shipping AI features end-to-end from prototype to production

Nice to have

• Experience with B2B data platforms, MDM, entity resolution or recommendation systems
• Exposure to fine-tuning LLMs (LoRA / QLoRA, PEFT, instruction tuning)
• Familiarity with Salesforce or Databricks ecosystems