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(Apply Now) Agentic AI Engineer

(Apply Now) Agentic AI Engineer

Acronotics LimitedIndia
5 hours ago
Job description

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

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