AI Solution Architect

Roles & 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 responsibilities

AI & GenAI solution architecture

• 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.

Production readiness & LLMOps design

• 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.

Safety governance & non-functional design

• 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.

Delivery & engagement support

• 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

• 1015 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 :

Educational qualification:

B.E/ or equivalent Qualification

Experience :

• 1015 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 :

Remote Work :

No

Employment Type :

Full-time