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Generative AI Systems Engineer Job Opening In Bengaluru – Now Hiring Acronotics Limited


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

Required Skill Profession

Computer Occupations


  • Job Details

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Unlock Your Generative AI Potential: Insight & Career Growth Guide


Real-time Generative AI Jobs Trends (Graphical Representation)

Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph here. Uncover the dynamic job market trends for Generative AI in Bengaluru, India, highlighting market share and opportunities for professionals in Generative AI roles.

104466 Jobs in India
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Are You Looking for Generative AI Systems Engineer Job?

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The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Acronotics Limited adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

1. Independence

2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying India laws and regulations

What Is the Average Salary Range for Generative AI Systems Engineer Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in Bengaluru. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

What Are the Key Qualifications for Generative AI Systems Engineer?

Key qualifications for Generative AI Systems Engineer typically include Computer Occupations and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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Interview Tips for Generative AI Systems Engineer Job Success

Acronotics Limited interview tips for Generative AI Systems Engineer

Here are some tips to help you prepare for and ace your Generative AI Systems Engineer job interview:

Before the Interview:

Research: Learn about the Acronotics Limited's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

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Follow Up: Send a thank-you email to the interviewer within 24 hours.

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Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your Generative AI Systems Engineer interview at Acronotics Limited, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Acronotics Limited's products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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