Agentic AI Engineer

Company Description

Acronotics Limited specializes in modern-age automation technologies such as Robotic Process Automation (RPA) and Artificial Intelligence (AI). We apply human intelligence to build cutting-edge robotic automation and AI solutions for our clients, transforming the way businesses operate. Our mission is to help clients design, develop, implement, and run truly transformative generative AI-based solutions.

Role Description

We are looking for a  skilled AI / ML Engineer  to help design and implement  GenAI-based systems  that interface with real-time enterprise data. You will be responsible for developing, fine-tuning, orchestrating, and integrating  LLM-powered capabilities  such as retrieval-augmented generation (RAG), function / tool calling, and data-grounded Q&A, within the  Azure OpenAI ecosystem .

The ideal candidate brings hands-on experience with  LLM orchestration frameworks , prompt engineering, embedding models, and integrating AI systems into production-grade Azure-based platforms.

Core Responsibilities

Development

Design and implement  LLM-based pipelines , including :

Prompt engineering

Few-shot and zero-shot techniques

Function / tool calling

Chain-of-thought and structured output generation

Work with  Azure OpenAI ,  GPT-4 , and embedding models for various use cases

Build conversational flows, decision trees, and fallback logic for copilots or assistants

Retrieval-Augmented Generation (RAG)

Develop and optimize  RAG pipelines :

Create embedding pipelines (e.g., using text-embedding-ada-002, Cohere, or Sentence Transformers)

Chunk and index content from structured and unstructured sources (PDFs, Office files, HTML, etc.)

Store and retrieve embeddings using  Azure AI Search ,  FAISS , or  Weaviate

Evaluate grounding accuracy and relevance scoring

Machine Learning Models

 Build, train, and fine-tune  time series forecasting models  (e.g., XGBoost, Prophet, ARIMA, or LSTM) for financial KPIs where GenAI requires predictive context

 Combine  structured model outputs with LLM reasoning  (e.g., forecasts + narrative insights)

Tool / Function Integration

Integrate structured data APIs, SQL endpoints, Power BI connectors, and OLAP cube access as  tools / functions  callable by the LLM

Design input / output schemas for safe and deterministic API usage by the model

Support plugin-style orchestration (LangChain / Function Calling / Semantic Kernel)

Evaluation & Iteration

Define custom  evaluation frameworks  using metrics like :

Hallucination rate

Grounding precision / recall

Prompt latency and token efficiency

Set up experiment tracking using tools like  MLflow ,  Weights & Biases , or  PromptLayer

Maintain few-shot / test prompt sets and continuously refine

Required Skills and Experience

3–6+ years of experience in AI / ML / NLP engineering

Deep familiarity with  LLM systems : prompt tuning, orchestration, and fine-tuning

Hands-on experience with :

Azure OpenAI Service

LangChain ,  Semantic Kernel , or similar orchestration tools

Vector databases  (Azure AI Search, FAISS, Pinecone)

Embedding model APIs (OpenAI, HuggingFace, Cohere, etc.)

Strong understanding of  time series modeling and ML forecasting techniques  in financial domains (e.g., cost, margin, working capital, price volatility)

Strong proficiency in  Python , with experience in developing modular, testable code for AI / ML pipelines, API integrations, and backend services

Experience building and deploying  backend components  (e.g. FastAPI, Flask) to serve AI models or integrate with retrieval pipelines

Familiarity with best practices for  production-grade AI applications , including logging, monitoring, and containerisation (e.g. Docker)

Ability to work across the full stack of an AI system – from model development to integration and inference APIs

Experience in building chatbots or copilots in enterprise settings

Knowledge of  Azure cloud services , esp.  Functions ,  App Services ,  Blob Storage , and  Key Vault

Familiarity with enterprise systems like  Power BI ,  SAP , or  OLAP cubes

Location

• Bangalore