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Principal Architect- Data Engineering (Gen AI)

Principal Architect- Data Engineering (Gen AI)

Tiger AnalyticsNagpur, IN
1 day ago
Job description

Title

Principal Architect – Data Engineering (Gen AI CoE)

Location : Chennai / Bangalore / Hyderabad

Experience : 15+

Employment Type : Full-Time

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 5000+ 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.

Role Overview :

As a Principal Data Architect – GenAI , you will lead the design and implementation of enterprise-scale Generative AI and data-driven intelligence solutions by combining your strong foundation in data engineering with cutting-edge AI technologies . You will play a key role in shaping the organization’s GenAI strategy, architecting end-to-end solutions that leverage large language models (LLMs), RAG, Agentic AI solution frameworks to drive innovations and solve complex Data Engineering problems for modern data platforms.

Building upon your prior experience in data architecture and engineering , you will design scalable data pipelines, ensure robust data governance, and enable accelerated development and modernization of traditional data ecosystems to modern data platform. You will also act as a trusted advisor to clients and internal teams, driving innovation and establishing best practices across GenAI solutioning.

Curious about the role?

  • Strategic, Leadership thinking, Dynamic mind, Proactive, eager to learn and pick-up new tech very quickly.
  • SME with Hands-On and Lead a small team for quick prototypes and PoCs, PoVs
  • Very strong skills in Python, with experience in building scalable and optimized applications with open-source libraries.
  • Very Strong understanding of Data Engineering concepts : Experience and understanding of
  • Designing and maintaining the data pipeline automations, Ingestion, data processing, optimizations ..etc.
  • Data structure & modelling
  • Data quality
  • Data governance
  • Operations
  • GenAI Experience :
  • Hands-on expertise with LLMs, Prompt Techniques, Retrieval-augmented generation (RAG) techniques
  • Strong in agentic AI solutions frameworks, AgentOps
  • Finetuning Open source LLMs and fine-tuning frameworks
  • Experience with Cloud & Platforms : Familiarity with AWS, GCP, Azure, Databricks and Snowflake

Educational Background :

  • Bachelor or Master’s degree in Computer Science, Engineering, or a related field
  • 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.

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