ST-L1- Tampa, FL

Infosys

About The Position

The Senior Technologist role is part of Infosys’ Strategic Technology Group (STG), which brings together experienced technologists to address complex, large-scale technology challenges. The role focuses on designing scalable architectures and frameworks, delivering reusable components and production-ready code, and applying technical judgment to support high-quality outcomes. The position also involves mentoring peers, influencing engineering practices, and helping teams adopt emerging technologies. The Senior Technologist will define end-to-end architectures for enterprise generative AI and agentic AI solutions, including single-agent and multi-agent systems, orchestration, Model Context Protocol (MCP) integrations, reusable AI skills, managed agents, and Retrieval-Augmented Generation (RAG). The role works across the AI development lifecycle and collaborates with data scientists, software engineers, and product managers to assess requirements and technical feasibility. It also supports proof-of-concept work, code reviews, responsible AI practices, test automation, and the resolution of technical risks and challenges. The position is based in Tampa, Florida. Relocation and/or travel to the work or project location may be required. Applicants must be authorized to work in the United States without employer-based visa sponsorship; Infosys cannot provide immigration sponsorship for this role.

Requirements

Core development experience and strong architecture and engineering knowledge.
Hands-on experience designing LLM-powered applications, AI agents, multi-agent systems, agent orchestration, MCP integrations, reusable AI skills, managed agents, and RAG solutions.
Proficiency in Python, FastAPI, and LangChain.
Working experience with AI cloud services such as Azure AI Services and OpenAI.
Ability to work comfortably in a fast-paced, agile environment.
Good collaboration and communication skills.
Bachelor’s degree or foreign equivalent from an accredited institution; three years of progressive specialty experience may substitute for each year of education.
Authorization to work in the United States for any employer without employer-based visa sponsorship.

Nice To Haves

Master’s degree in computer science, artificial intelligence, or a related field, or equivalent experience.
Experience with cloud-based platforms such as Azure and Microsoft/Azure AI services.
Experience fine-tuning open-source AI models.
Strong understanding of one or more domains and associated industry standards.
Industry-acclaimed external certifications, if applicable.
Active participation in technology forums.
Contributions to the open-source community.

Responsibilities

Evaluate project requirements and use cases and deliver high-quality designs, frameworks, and production-ready code.
Design technology frameworks for complex scenarios, develop design patterns and reference implementations, create reusable assets, and conduct design reviews.
Deliver high-quality code across applications, databases, and integrations.
Optimize code, debug complex routines, and develop code generators and pilot implementations for reusable components.
Work with other teams to align project goals and technology implementations.
Provide technical guidance to peers and help maintain delivery consistency and code quality.
Identify emerging programming technologies and independently develop proof-of-concepts for new technologies and complex modules.
Provide input for high-risk deployments involving multiple technologies and programming languages.
Evaluate and implement technical services that meet quality-of-service requirements and align with business and IT KPIs.
Create reusable assets and deliver defect-free code that meets quality benchmarks and Zero-Defect Delivery goals.
Resolve technical challenges in complex projects and reduce risk exposure.
Monitor emerging technologies and industry trends to inform decisions and improve project outcomes.
Support test automation and execute test strategies to improve quality.
Define end-to-end architectures for enterprise GenAI and agentic AI solutions.
Design single-agent and multi-agent architectures, including orchestration, routing, delegation, handoffs, collaboration, and human-in-the-loop patterns.
Design secure MCP integration architectures that expose enterprise data, APIs, tools, and capabilities to AI agents.
Define reusable skills, tools, prompts, and agent capabilities for use across agents and business use cases.
Design solutions using managed or hosted agents and enterprise AI platforms.
Evaluate and recommend agent orchestration frameworks such as LangGraph, LangChain, AutoGen, and Semantic Kernel, or equivalents.
Establish architectural controls for guardrails, security, observability, logging, tracing, governance, auditability, and responsible AI.
Take ownership of stages of the AI development lifecycle, such as data preprocessing, model training, evaluation, optimization, or deployment, and understand how they connect end to end.
Collaborate with data scientists, software engineers, and product managers to understand requirements and raise technical feasibility concerns early.
Stay current with generative AI research and share learnings with the team.
Promote responsible AI practices, including awareness of bias mitigation, fairness, and traceability.
Participate in code reviews as both a reviewer and recipient of feedback.
Support proofs of concept for new technologies and take responsibility for defined portions of the work.