GenAI Testing Consultant/Architect

Job DescriptionStep into a high-impact role where you'll shape how Generative AI systems are envisioned, validated, trusted, and scaled in real-world enterprise environments. As a senior technology consultant and architect, you will partner with business, product, and engineering stakeholders to run discovery workshops, define success metrics, and create solution roadmaps for high-value GenAI and ML use cases. You'll blend hands-on technical depth with architecture leadership-guiding teams from experimentation to production-grade systems-while designing robust testing strategies for GenAI solutions covering quality, safety, reliability, and performance. You'll work hands-on with data scientists, ML engineers, and cloud teams to build repeatable evaluation frameworks, automate testing pipelines, and guide stakeholders through best practices for responsible AI adoption. If you enjoy translating complex needs into elegant AI architectures, solving ambiguous problems, mentoring teams, and building solutions that are secure, reliable, and measurable, this role offers the right blend of innovation, ownership, and collaboration.
Roles & 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.
Technical Requirement

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.
Additional ResponsibilityGood to have skills:GenAI, Python, Agile methodologies, CI/CD pipelines, API testing, SQL/Database basics
Location: BANGALORE, PUNE, HYDERABAD, CHENNAI, TVM, INDORE, NAGPUR, MLR, MYS, NOIDA, BBSR, KOLKATA, COIMBATORE, HUBLI
Educational RequirementBachelor of Engineering
Preferred SkillsTechnology->AI-Generative AI->Prompt Engineering,Technology->AI-Agentic AI->Agent Engineering,Technology->Open System->Open System- ALL->Python,Technology->Testing Technologyes->Test Automation Technology,Technology->AI-Generative AI->Generative AI - Basic->retrieval augmented generation (rag)
Service LineInfosys Quality Engineering