Chennai, Bangalore, Hyderabad,   Pune, NCR

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.

In   this role, you will build LLM-powered applications such as   retrieval-augmented systems, agentic workflows, with a strong focus on   scalability, reliability, and real-world impact. Also, you will work on internal   product development and support client-focused projects, with exposure to the   pharma domain being a plus.

You'll collaborate with experienced team   members and learn to create impactful AI solutions while optimizing and   developing GenAI applications.

Your responsibilities will include:

- Supporting the design, development, and deployment of GenAI solutions,   learning to address challenges like hallucinations, bias, and latency, while   contributing to performance and reliability improvements.

- Collaborating with both internal teams and external stakeholders,   particularly in the pharma space, to understand business requirements and   contribute to the development of tailored AI-powered systems.

- Assisting in the full lifecycle of AI project delivery, including   ideation, model fine-tuning, deployment, and performance monitoring under the   guidance of senior team members.

- Learning and applying fine-tuning techniques (such as LoRA, PEFT) to   Large Language Models (LLMs) for specific business needs.

- Assisting in the development of scalable pipelines for AI model   deployment, including handling error management, monitoring, and retraining   strategies.

- Actively participating in a collaborative environment, sharing ideas   and working as part of a dynamic team of data scientists and AI engineers.

- Design and   deploy NLP and GenAI solutions using LLMs, fine-tuning techniques (LoRA,   PEFT), and AI-powered automation.

- Build and   optimize LLM-powered chatbots, virtual assistants, and AI agents with high   accuracy and contextual awareness.

- Implement   agentic AI systems enabling autonomous, multi-step workflows using   orchestration frameworks (LangChain, LlamaIndex, AutoGen, etc.).

- Architect   scalable NLP pipelines covering text preprocessing, entity recognition (NER),   summarization, Q&A, and conversational AI.

- Lead research   and implementation of advanced GenAI techniques: LLMs, Agentic Solutioning, transformers,   embeddings, RAG, and multi-modal models.

- Optimize   inference pipelines using quantization, model distillation, and   retrieval-enhanced generation for performance and cost efficiency.

- Develop   scalable model deployment pipelines with robust error handling, monitoring,   and retraining strategies.

- Ensure LLM   observability and guardrails - covering model monitoring, safety, fairness,   and regulatory compliance.

- Lead MLOps   practices: CI/CD pipelines, containerization (Docker, Kubernetes), and cloud   deployments on AWS, GCP, or Azure.

- Collaborate   with cross-functional teams to integrate GenAI solutions into enterprise   applications via robust APIs and microservices.

- Work with   internal teams and external stakeholders (including pharma clients) to   translate business requirements into AI solutions.

- Mentor junior   engineers, champion AI best practices, and contribute to AI governance   frameworks in regulated industries.

- 5-7.5 years in NLP, Generative AI, or related ML discipline.

- 2+ years working with GenAI/LLMs in production systems.

- Deep expertise in LLMs, transformer architecture, Agentic Frameworks and   fine-tuning techniques.

- Strong knowledge of NLP pipelines, including text preprocessing,   tokenization, embeddings, and named entity recognition (NER).

- Experience with retrieval-augmented generation (RAG), vector databases,   (FAISS, Pinecone, ChromaDB), and prompt engineering.

- Hands-on experience with Agentic AI systems, LLM observability tools,   and AI safety guardrails.

- Proficiency in Python and backend development (Django/Flask   preferred), with strong API and microservices expertise.

- Familiarity with MLOps, cloud platforms (AWS, GCP, Azure), and   scalable model deployment strategies.

- Prior experience in life sciences, pharma, or other regulated   industries is a plus.

- A problem-solving mindset with the ability to work independently,   drive innovation, and mentor junior engineers.

- Opportunity to work on real-world, production-grade GenAI systems at   enterprise scale.

- Exposure to diverse industries and high-impact problem statements.

- A strong ecosystem of AI practitioners, accelerators, and   innovation-led culture.

- Ability to shape next-generation AI solutions beyond prototypes.

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.