AI Solution Architect

Robert Bosch Group; Bengaluru; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Bosch Global Software Technologies Private Limited is seeking an experienced Solution Architect for AI and GenAI engagements in Bengaluru. You will own the technical design from opportunity through delivery and guide engineering teams on AI architecture decisions, data foundations and security requirements.

This role requires 10–15 years in software/ML engineering with production AI ownership, and strong hands-on GenAI, MLOps, and observability capabilities.

Qualifications

• Strong hands-on GenAI architecture including LLMs, RAG, agentic patterns and orchestration frameworks.
• Classical ML delivery grounding and production readiness.
• MLOps/LLMOps, evaluation design and model serving.
• Experience with responsible AI, security and compliance requirements.
• Working knowledge of data platforms, pipelines and modelling.
• Exposure to Enterprise Architecture is an added advantage.
• Ability to lead technical workshops with client stakeholders.
• Excellent verbal and written communication of technical trade-offs.

Responsibilities

• Own end-to-end AI/GenAI architecture for engagements, including classical ML and LLM applications.
• Make design decisions on build vs. buy, model selection, fine-tuning vs retrieval, and orchestration patterns.
• Design retrieval architectures (embedding, indexing, hybrid search) for accuracy and latency.
• Architect agentic systems with tool use, memory and multi-step orchestration.
• Set up LLMOps/MLOps pipelines, deployment, versioning and rollback.
• Define evaluation architecture with eval harnesses and quality benchmarks.
• Ensure observability, monitoring and drift detection; enable handoff to Managed Ops.
• Design cost-efficient inference architectures and FinOps guardrails.
• Specify data requirements for AI solutions and collaborate on data platform design.
• Embed Responsible AI and AI security standards into solution design.

Skills

GenAI architecture

LLMs

RAG

Orchestration frameworks

Langchain

Haystack

Llama Index

ML engineering

MLOps/LLMOps

Evaluation design

Model serving

Observability

Cost optimisation

Responsible AI

Security & Compliance

Education

B.E/B.Tech/MCA/PhD or equivalent

Tools

Langchain

Haystack

Llama Index

Job description

• Legal Entity: Bosch Global Software Technologies Private Limited

Company Description

Bosch Global Software Technologies Private Limitedis 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

This role architects production-ready AI and GenAI solutions that are reliable, observable, safe, and cost-efficient. The architect owns the technical design of AI solutions from opportunity through delivery. The solution architect is the senior technical authority on AI architecture decisions within projects and collaborates with the Data Solution Architect where engagements span both data foundations and AI solutions.

Key responsibilities

Own end-to-end architecture for AI and GenAI engagements — classical ML, LLM applications, RAG systems, and agentic workflows.

Responsible for design decisions: build vs. buy, model selection, fine-tuning vs. retrieval, and orchestration patterns.

Design retrieval architectures (chunking, embedding, indexing, hybrid search, and re-ranking) for accuracy and latency at scale.

Architect agentic systems: tool use, memory, multi-step orchestration, and human-in-the-loop control points.

Design LLMOps/MLOps setup for engagements: model serving, versioning, deployment pipelines, and rollback.

Define evaluation architecture: eval harnesses, quality benchmarks, regression testing, and acceptance criteria.

Architect observability, monitoring, and drift detection; design for operability and handoff to Managed Ops.

Design cost-efficient inference architectures: model tiering, caching, token economics, and FinOps guardrails.

Data foundations for AI

Specify the data requirements for AI solutions — training data, feature pipelines etc.

Partner with Data Solution Architects to translate model and RAG requirements into data platform design.

Design embedding and vector store strategy in sync with the underlying data architecture.

Embed Responsible AI and AI security standards into solution design — guardrails, explainability requirements, and human oversight.

Design against GenAI risk surfaces: prompt injection, data leakage, unsafe outputs, and insecure tool use.

Design for non-functional requirements: latency, scalability, availability, security, and cost. Ensure designs meet regulatory obligations.

Serve as technical authority through delivery — guiding engineering teams, reviewing designs, and resolving technical escalations.

Support pursuits with technical proposals, effort estimation, and technical workshops with client stakeholders.

Experience

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

Expected Skills

Strong Hands-on GenAI architecture — LLMs, RAG, agentic patterns, orchestration frameworks and tools such as Langchain, Haystack, and Llama Index

Classical ML delivery grounding

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

Practical experience designing to Responsible AI, security, and compliance requirements

Working knowledge of data platforms, pipelines, and modelling.

Exposure to Enterprise Architecture is an added advantage

Ability to lead technical workshops with technical stakeholders in client environment

Excellent verbal and written communication, technical authoring, ability to communicate technical concepts and trade-offs to stakeholders of varying technical competency

Qualifications

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

Experience :

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

Mandatory/requires Skills :

• Strong Hands-on GenAI architecture — LLMs, RAG, agentic patterns, orchestration frameworks and tools such as Langchain, Haystack, and Llama Index
• Classical ML delivery grounding
• MLOps/LLMOps, evaluation design, model serving, observability, and inference cost optimisation
• Practical experience designing to Responsible AI, security, and compliance requirements
• Working knowledge of data platforms, pipelines, and modelling.
• Exposure to Enterprise Architecture is an added advantage
• Ability to lead technical workshops with technical stakeholders in client environment
• Excellent verbal and written communication, technical authoring, ability to communicate technical concepts and trade-offs to stakeholders of varying technical competency

Preferred Skills :