Senior Artificial Intelligence Engineer

Hrassistance India Consultancy Llp; Chennai District, Hyderabad; On-site; INR 1,500,000 - 2,800,000; Full time

Job summary

Hrassistance India Consultancy Llp is seeking an experienced AI Engineer to design and operationalize AI-driven solutions for a global analytics organization.

The role emphasizes hands-on work with Python, PySpark, GenAI frameworks, LLMs, RAG, vector search, and agentic workflows using LangChain and LangGraph, across cloud and hybrid environments.

You will collaborate with Data Scientists and stakeholders to productionize GenAI capabilities and build scalable, reliable AI systems.

Qualifications

• 58 years of experience in AI/ML Engineering, Data Science, or Software Engineering, with at least 2 years of hands-on Generative AI experience.

Responsibilities

• Design and develop agentic workflows using LangChain and LangGraph.
• Build autonomous AI agents for data validation, reporting automation, document processing, and domain-specific workflows.
• Deploy scalable agent pipelines with monitoring and evaluation mechanisms.
• Develop GenAI applications using GPT, Gemini, and LLaMA.
• Collaborate with Data Scientists to productionize AI/ML Proofs of Concepts (POCs).

Skills

AI/ML Engineering

Python

PySpark

API Development

LangChain

LangGraph

Hugging Face Transformers

OpenAI SDK

Azure OpenAI

Tools

LangChain library

LangGraph

Hugging Face Transformers

OpenAI SDK

AWS

Azure

GCP

Job description

Job Description: AI Engineer (GenAI / Agentic AI)

Role Overview

We are looking for an experienced AI Engineer to design, develop, and operationalize AI-driven solutions for our global Analytics organization.

The ideal candidate should have strong hands-on expertise in Python, PySpark, Agentic Workflow Development, and Generative AI frameworks, with experience building scalable applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector search, and automation pipelines.

The candidate will collaborate with Data Scientists, MLOps Engineers, and Business Stakeholders to build production-grade intelligent systems aligned with the organizations Generative AI roadmap.

Key Responsibilities

1. Agent Development & Architecture

• Design and develop agentic workflows using LangChain, LangGraph, and similar frameworks.
• Build autonomous AI agents for:
  
• Data validation
• Reporting automation
• Document processing
• Domain-specific workflows
• Deploy scalable and resilient agent pipelines with proper monitoring and evaluation mechanisms.

2. Generative AI Application Engineering

• Develop GenAI applications using LLM models such as:
  
• GPT
• Gemini
• LLaMA
• Implement and optimize:
  
• Retrieval-Augmented Generation (RAG)
• Vector Search
• Prompt Engineering and Orchestration
• Model Evaluation Frameworks
• Collaborate with Data Scientists to productionize AI/ML Proof of Concepts (POCs).

3. Data & Platform Engineering

• Build distributed data processing pipelines using Python and PySpark.
• Develop APIs, SDKs, and integration layers for AI-powered applications.
• Optimize AI systems for performance, scalability, and reliability across cloud and hybrid environments.

4. MLOps / LLMOps

• Contribute to AI model CI/CD workflows including:
  
• Deployment
• Testing
• Monitoring
• Version management
• Implement governance frameworks, guardrails, and reusable GenAI components.
• Support production monitoring and continuous improvement of AI solutions.

5. Collaboration & Stakeholder Management

• Work closely with Analytics, Product, Engineering, and Business teams to define and deliver AI solutions.
• Participate in architecture discussions, design reviews, and iterative development cycles.
• Contribute to knowledge sharing and GenAI capability building within the organization.

Required Skills & Qualifications

• 58 years of experience in AI/ML Engineering, Data Science, or Software Engineering, with at least 2 years of hands-on Generative AI experience.
• Strong programming expertise in:
  
• Python
• PySpark
• API Development
• Hands-on experience with LLM frameworks and platforms:
  
• LangChain
• LangGraph
• Hugging Face Transformers
• OpenAI SDK
• Azure OpenAI / Vertex AI / AWS Bedrock
• Experience developing:
  
• AI Agents
• Retrieval pipelines
• Tool-calling workflows
• Autonomous task orchestration systems
• Strong understanding of GenAI concepts:
  
• Prompt Engineering
• Embeddings
• RAG Architecture
• Vector Databases
• Model Evaluation Metrics
• Hallucination Detection and Mitigation
• Model Selection
• Fine-tuningnonimalty not used
• Context Engineering
• Experience with cloud platforms:
  
• AWS
• Azure
• GCP
• Experience with:
  
• Docker
• CI/CD pipelines
• AI/ML deployment practices
• Strong problem-solving skills with system design and architecture thinking.
• Excellent verbal, written communication, and presentation skills.

Good to Have Skills

• Experience in workflow automation and building reusable AI components.
• Background in analytics, statistical modelling, or enterprise data products.
• Experience with MLOps / LLMOps tools and frameworks.
• Experience building enterprise-scale AI solutions.