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Data and AI Products Architect

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Onsite

Data and AI Products Architect

Bosch

Data and AI Products Architect

Skills

Product StrategyMachine LearningAICompliance

2 months ago

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Important information


Contract type:

Permanent

Location:

Karnataka, India

Work mode:

Onsite

Published on:

10 August 2026

What they need


Company Description

Bosch Global Software Technologies Private Limited is a 100% owned subsidiary of Robert Bosch GmbH, one of the world's leading global supplier of technology and services, offering end-to-end Engineering, IT and Business Solutions. With over 27,000+ associates, it’s the largest software development center of Bosch, outside Germany, indicating that it is the Technology Powerhouse of Bosch in India with a global footprint and presence in the US, Europe and the Asia Pacific region.

Job Description

Role Overview

This role owns the technical architecture of the Data & AI product portfolio and acts as the Technical counterpart to the Product Owner. Works with Innovation on PoC-to-product transitions and applies AI governance and Responsible AI standards. Responsible for architecting products for multi-tenancy and non-functional characteristics.

Key responsibilities

Product architecture & portfolio

  • Own the target architecture for each product in the portfolio, designing for reuse, configurability, and multi-tenancy.
  • Define the shared platform layer — common services, components, and infrastructure reusable across products — and drive consolidation of duplicated capability.
  • Own architecture roadmap in sync with product roadmap.

AI & GenAI solution design

  • Responsible for design decisions: build vs. buy, model selection, fine-tuning vs. retrieval, technical debt management and trade-offs.
  • Design retrieval architectures (chunking, embedding, indexing, hybrid search, and re-ranking) for accuracy and latency at scale.
  • Define the data architecture for AI solutions — training data, feature pipelines etc.
  • Architect observability, monitoring, and drift detection

Product maturation and disposition

  • Assess PoCs and early MVPs for technical viability, scalability, and productisation.
  • Conduct product technical readiness assessments; provide the architectural basis for product disposition decisions.

Production readiness & unit economics

  • Design the LLMOps/MLOps backbone for the portfolio — serving, versioning, deployment pipelines, and rollback.
  • Define evaluation architecture: eval harnesses, quality benchmarks, regression testing.
  • Own the cost model — inference economics and token cost — as an input to product pricing.

Safety, governance & technical leadership

  • Embed Responsible AI, explainability, and AI security standards into product designs. Design for the regulatory obligations.
  • Support the Product Owner with technical input to funding pitches, business cases, and customer conversations.

Experience

  • 10–15 years in software/ML engineering and architecture, with proven AI solutions in production

Expected Skills

  • GenAI architecture — LLMs, RAG, agentic patterns, orchestration frameworks
  • MLOps/LLMOps, evaluation design, model serving, observability, and inference cost optimisation
  • Experience in architecting commercial software products - Multi-tenancy, versioning, and productisation of prototypes
  • Working knowledge of data platforms, pipelines, and modelling
  • Ability to connect architectural choices to unit economics, profitability and time-to-market
  • Guide the product development teams with implementation and standards compliance

Qualifications

Educational qualification:

B.E/B.Tech/MCA/Phd or equivalent Qualification

Experience :

  • 10–15 years in software/ML engineering and architecture, with proven AI solutions in production

Mandatory/requires Skills :

  • GenAI architecture — LLMs, RAG, agentic patterns, orchestration frameworks

  • MLOps/LLMOps, evaluation design, model serving, observability, and inference cost optimisation

  • Experience in architecting commercial software products - Multi-tenancy, versioning, and productisation of prototypes

  • Working knowledge of data platforms, pipelines, and modelling

  • Ability to connect architectural choices to unit economics, profitability and time-to-market

  • Guide the product development teams with implementation and standards compliance

Preferred Skills :

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