AI Solution ArchitectFull-timeLegal Entity: Bosch Global Software Technologies Private LimitedCompany DescriptionBosch 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 DescriptionRoles & Responsibilities :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 responsibilitiesAI & GenAI solution architectureOwn 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.Production readiness & LLMOps designDesign 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 AISpecify 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.Safety, governance & non-functional designEmbed 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.Delivery & engagement supportServe 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.Experience10–15 years in software/ML engineering and architecture, with proven ownership of AI solutions in productionExpected SkillsStrong Hands-on GenAI architecture — LLMs, RAG, agentic patterns, orchestration frameworks and tools such as Langchain, Haystack, and Llama IndexClassical ML delivery groundingMLOps/LLMOps, evaluation design, model serving, observability, and inference cost optimisationPractical experience designing to Responsible AI, security, and compliance requirementsWorking knowledge of data platforms, pipelines, and modelling.Exposure to Enterprise Architecture is an added advantageAbility to lead technical workshops with technical stakeholders in client environmentExcellent verbal and written communication, technical authoring, ability to communicate technical concepts and trade-offs to stakeholders of varying technical competencyQualificationsEducational qualification:B.E/B.Tech/MCA/PhD or equivalent QualificationExperience :10–15 years in software/ML engineering and architecture, with proven ownership of AI solutions in productionMandatory/requires Skills :Strong Hands-on GenAI architecture — LLMs, RAG, agentic patterns, orchestration frameworks and tools such as Langchain, Haystack, and Llama IndexClassical ML delivery groundingMLOps/LLMOps, evaluation design, model serving, observability, and inference cost optimisationPractical experience designing to Responsible AI, security, and compliance requirementsWorking knowledge of data platforms, pipelines, and modelling.Exposure to Enterprise Architecture is an added advantageAbility to lead technical workshops with technical stakeholders in client environmentExcellent verbal and written communication, technical authoring, ability to communicate technical concepts and trade-offs to stakeholders of varying technical competencyPreferred Skills :By clicking the link above or any third-party link within this posting, you are leaving this site and going to a third-party website where the third-party website's terms and privacy policy applyI'm interestedI'm interestedPrivacy NoticeImprint
