brand logo
View All Jobs

AI Engineer – Senior / Lead / Staff

Bangalore, Hyderabad
Job Description
Title:  AI Engineer – Senior / Lead / Staff
Location: 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™ (2022-25), 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.

Curious about the role? What your typical day would look like? 

As an AI engineer specializing in Agents, Generative AI, and Machine Learning Engineering (MLE), you will be at the forefront of AI innovation. Your role will involve designing, building, deploying, and operationalizing solutions for business problems across industries using large language models (LLMs) and agents. You will be part of the core AI solution development team and work closely with product development, platform engineering and enterprise architecture teams.

Your Key Responsibilities:
 ● Agents, Generative AI, NLP & AIOps: Design, develop, deploy, and scale advanced applications  using LLMs (e.g., GPT, Gemini, LLaMA, Mistral), agent orchestration engines (e.g., LangGraph,  AI foundry, Databricks Agent Bricks, ADK) NLP methods, and AIops best practices to build  solutions to solve business problems. 
● AI Engineering & Deployment: Implement end-to-end AI pipelines—including data preprocessing, model training, versioning, testing, and deployment—using tools like MLflow,  Docker, Kubernetes, and CI/CD practices. 
● Innovative Problem Solving: Leverage cutting-edge AI and ML methodologies to solve practical  business problems and deliver measurable results
Scalable AI Solutions: Ensure robust deployment, monitoring, and retraining of models in  production environments, working closely with data engineering and platform teams.
 ● Data-Driven Insights: Conduct deep analysis of structured and unstructured data to uncover  trends, guide decisions, and optimize AI models. 
● Cross-Functional Collaboration: Partner with Consulting, Engineering, and Platform teams to  integrate AI/ML solutions into broader architectures and business strategies.

What do we expect?

• Overall, 4-12 years of experience with real-time experience in AI, ML with recent experience  in Agents, GenAI and AIOps. 
• Expertise in Generative AI: Significant hands-on experience in building and deploying  solutions using LLMs, Agents to solve business problems 
• Hands-on experience with building and optimizing RAG agents, enterprise search  applications, large scale unstructured data processing, prompt tuning, and setting up event  driven architectures
 • Production Readiness: Proven experience in deploying and scaling Gen AI, agents and  other ML models including experience in performance optimization 
• Deployment Tools & Best Practices: Strong experience in Devops and associated  technology such as containerization (Docker), orchestration (Kubernetes), model monitoring and cloud platforms (AWS/GCP/Azure) for deploying AI solutions at scale. 
• Expertise in Software development using Python including using frameworks (such as  Django/Flask) or other similar technologies.
• In-depth understanding and experience building APIs and microservices 
 • Innovation & Curiosity: A passion for staying updated with the latest in Gen AI, LLMs, and  ML engineering practices.
 • Communication: Ability to translate complex technical concepts into business-friendly  insights and recommendations. 
• Eagerness to rapidly prototype ideas, experiment, and turn them into real-world solutions  that can scale. 
• Excited to explore emerging technology and frameworks in agentic and Gen AI  technology areas

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. 


Job Requirement
What do we expect?
• Overall, 4-12 years of experience with real-time experience in AI, ML with recent experience  in Agents, GenAI and AIOps.
• Expertise in Generative AI: Significant hands-on experience in building and deploying  solutions using LLMs, Agents to solve business problems
• Hands-on experience with building and optimizing RAG agents, enterprise search  applications, large scale unstructured data processing, prompt tuning, and setting up event  driven architectures
• Production Readiness: Proven experience in deploying and scaling Gen AI, agents and  other ML models including experience in performance optimization
• Deployment Tools & Best Practices: Strong experience in Devops and associated  technology such as containerization (Docker), orchestration (Kubernetes), model monitoring and cloud platforms (AWS/GCP/Azure) for deploying AI solutions at scale.
• Expertise in Software development using Python including using frameworks (such as  Django/Flask) or other similar technologies.
• In-depth understanding and experience building APIs and microservices
• Innovation & Curiosity: A passion for staying updated with the latest in Gen AI, LLMs, and  ML engineering practices.
• Communication: Ability to translate complex technical concepts into business-friendly  insights and recommendations.
• Eagerness to rapidly prototype ideas, experiment, and turn them into real-world solutions  that can scale.
• Excited to explore emerging technology and frameworks in agentic and Gen AI  technology areas