Lead AIML Engineer - Python+GenAI

Job Title : Lead AIML Engineer - Python+GenAI

Location : Chennai, Bangalore, Hyderabad

Who we are

Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer full-stack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow.

Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. Many of our team leaders rank in Top 10 and 40 Under 40 lists, exemplifying our dedication to innovation and excellence.

We are a Great Place to Work-Certified™ (2022-24), recognized by analyst firms such as Forrester, Gartner, HFS, Everest, ISG and others. We have been ranked among the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine

About the Role:

We are seeking a highly skilled Python Developer with hands-on experience in Generative AI to design, develop, and deploy AI-powered applications. The ideal candidate will have strong expertise in Python programming, experience working with Large Language Models (LLMs), and the ability to build scalable AI solutions using modern frameworks and cloud technologies.

You will collaborate with cross-functional teams to develop intelligent applications, automate business processes, and integrate GenAI capabilities into enterprise platforms.

Key Responsibilities:

• Design, develop, test, and maintain scalable Python applications.
• Build and deploy Generative AI solutions using Large Language Models (LLMs).
• Develop AI-powered applications such as chatbots, virtual assistants, document intelligence, and workflow automation solutions.
• Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases.
• Integrate AI models through APIs from providers such as OpenAI, Anthropic, Google Gemini, Azure OpenAI, or open-source LLMs.
• Develop prompt engineering strategies to improve model performance and response quality.
• Build AI agents using frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, or similar orchestration frameworks.
• Optimize AI application performance, latency, scalability, and cost.
• Create RESTful APIs using FastAPI, Flask, or Django.
• Work with structured and unstructured data for AI model integration.
• Collaborate with product managers, data scientists, and DevOps teams throughout the software development lifecycle.
• Write clean, maintainable, and well-documented code following best practices.
• Participate in code reviews, architecture discussions, and technical design sessions.
• Stay current with advancements in Python, Generative AI, LLMs, and AI engineering best practices.

Required Qualifications:

• Expert-level proficiency in Python.
• Strong understanding of object-oriented programming (OOP), data structures, algorithms, and design patterns.
• Experience with multithreading, multiprocessing, asynchronous programming (asyncio), and performance optimization.
• Experience building REST APIs using FastAPI, Flask, or Django.
• Knowledge of testing frameworks such as PyTest or UnitTest.
• Hands-on experience developing applications using Large Language Models (LLMs).
• Experience with prompt engineering and prompt optimization.
• Strong understanding of Retrieval-Augmented Generation (RAG).
• Experience with vector databases such as Pinecone, FAISS, Chroma, Milvus, or Weaviate.
• Experience using AI orchestration frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, or Semantic Kernel.
• Experience integrating OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, or open-source models (Llama, Mistral, DeepSeek, etc.).
• Familiarity with AI agents, function/tool calling, memory management, and agent orchestration.
• Understanding of model evaluation, guardrails, hallucination mitigation, and responsible AI practices.

Databases

• PostgreSQL
• MySQL
• MongoDB
• Redis
• Vector Databases

Cloud & DevOps

• AWS, Azure, or Google Cloud Platform
• Docker
• Kubernetes (preferred)
• CI/CD pipelines
• Git/GitHub/GitLab

You are important to us, let’s stay connected!

Every individual comes with a different set of skills and qualities so even if you don’t tick all the boxes for the role today, we urge you to apply as there might be a suitable/unique role for you tomorrow. We are an equal opportunity employer. Our diverse and inclusive culture and values guide us to listen, trust, respect, and encourage people to grow the way they desire.

Note: The designation will be commensurate with expertise and experience. Compensation packages are among the best in the industry.

Additional Benefits: Health insurance (self & family), virtual wellness platform, and knowledge communities

Mandatory Skills

Machine Learning,Artificial Intelligence,Natural Language Processing,Python,generative ai

Role

Key Responsibilities:

• Design, develop, test, and maintain scalable Python applications.
• Build and deploy Generative AI solutions using Large Language Models (LLMs).
• Develop AI-powered applications such as chatbots, virtual assistants, document intelligence, and workflow automation solutions.
• Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases.
• Integrate AI models through APIs from providers such as OpenAI, Anthropic, Google Gemini, Azure OpenAI, or open-source LLMs.
• Develop prompt engineering strategies to improve model performance and response quality.
• Build AI agents using frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, or similar orchestration frameworks.
• Optimize AI application performance, latency, scalability, and cost.
• Create RESTful APIs using FastAPI, Flask, or Django.
• Work with structured and unstructured data for AI model integration.
• Collaborate with product managers, data scientists, and DevOps teams throughout the software development lifecycle.
• Write clean, maintainable, and well-documented code following best practices.
• Participate in code reviews, architecture discussions, and technical design sessions.
• Stay current with advancements in Python, Generative AI, LLMs, and AI engineering best practices.

Education Qualification

B.E/B.Tech

Experience

7 to 10 years