GenAI Testing Consultant / Architect
- Infosys
- 5 - 10 years
- Bengaluru
- 21 days ago
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Job Description
Educational Requirements
Bachelor of Engineering
Service Line
Infosys Quality Engineering
Responsibilities
- Lead discovery workshops to identify high-value GenAI and ML use cases, define success metrics (standard and custom), and create solution roadmaps
- Architect end-to-end Generative AI systems, including data pipelines, model selection, orchestration, evaluation, and deployment patterns using Infosys and industry-standard tools and platforms
- Design and implement ML/AI solutions using Python (or other relevant Data Science/AI languages), applying strong software engineering practices for maintainability, performance, and reliability
- Build MCP and agentic-based solutions using appropriate frameworks, enabling tool/function calling, workflow orchestration, and multi-step reasoning patterns aligned to business needs
- Test and validate GenAI applications using relevant tools and frameworks; capture, analyze, and report standard and custom quality metrics (e g , relevance, groundedness, toxicity, latency, cost) and drive continuous improvement
- Collaborate with cloud and platform teams to design scalable Cloud AI architectures and cost-efficient deployments across AWS, Azure, or GCP
- Explore and evaluate new technologies, tools, and testing methodologies to improve development processes and solution quality; stay up-to-date with advancements in Generative AI and evaluation practices
Additional Responsibilities:
Good to have skills: Agile methodologies, CI/CD pipelines, API testing, SQL/Database basicsLocation: BANGALORE, PUNE, HYDERABAD, CHENNAI, TVM, INDORE, NAGPUR, MLR, MYS, NOIDA, BBSR, KOLKATA, COIMBATORE, HUBLI
Technical and Professional Requirements:
- Experience architecting Cloud AI solutions, including scalable inference, data security patterns, and cost/performance optimization
- Hands-on experience with LLM application patterns such as RAG, tool/function calling, prompt engineering, and automated evaluation frameworks
- Strong MLOps/LLMOps expertise: experiment tracking, model registry, CI/CD, observability, drift detection, and incident response for AI services
- Experience with data engineering concepts (feature stores, batch/stream processing) to support ML and GenAI workloads
- Proven ability to lead architecture governance, create reference architectures, and drive adoption across teams and portfolios
Preferred Skills:
Technology->Cloud Testing->Cloud Testing - ALL
Technology->data science->PYTHON
Technology->Data Science->Machine Learning
Technology->Machine Learning->Generative AI
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: DevOpsRole: DevOps Consultant / ArchitectEmployement Type: Full timeContact Details:
Company: InfosysLocation(s): Bengaluru+ View Contact
Keyskills: llm mlops python data pipelines workflow orchestration ai machine learning data engineering sql incident response data science gcp use cases software engineering agile performance optimization aws api testing architecture azure
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