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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - **Company:** Infosys - **Location:** Charlotte, NC, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Cyber Security, Continuous Integration, Elasticsearch, Github, Design of User Interfaces, Python (Programming Language), OpenShift, Redis, Search Technologies, Secure Coding, Software Deployment, Software Engineering, TypeScript, User-Centered Design, Chatbots, GitHub Copilot, ReactJS, Delivery Pipeline, Large Language Models, Multi-Agent Systems, Prompt Engineering, Model Validation, Generative AI, Backend, Kubernetes, Deployment Automation, Machine Learning Operations, Front End Software Development - **Published:** June 5, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=56fecfae6dbcd703 ## About the Role Do you have experience in TypeScript?, * 10+ years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education * Expert-level proficiency in: + Python (AI/ML, backend, orchestration) + TypeScript and modern React frameworks * Experience building solutions using: + OpenAI, Anthropic, Google (Vertex AI), GitHub Copilot / GitHub ecosystem * Hands-on experience deploying applications using: + OCP/OpenShift, , Kubernetes, CI/CD pipelines * Proven ability to lead multiple engineering pods and mentor engineers across levels. * Comfortable executing Agile methodologies across short sprint cycles. * Strong understanding of: + Cybersecurity controls + Model risk management + Compliance requirements in regulated financial-services environments, * Experience building high-availability banking or financial applications. * Familiarity with vector databases, embeddings, search systems (e.g., ChromaDB,, Elasticsearch, Redis Vector). * Understanding of evaluation frameworks for LLM outputs (hallucination detection, guardrails, red-teaming). * Exposure to MLOps fundamentals and responsible AI concepts. ## Description * Lead end-to-end design and development of AI systems including chatbots, Retrieval Augmented Generation (RAG) platforms, autonomous agents, and workflow automation tools. * Drive complex, multi-domain AI initiatives, ensuring technical excellence across backend services, front-end experiences, and AI model integrations. * Architect scalable and secure, AI solutions leveraging Google, OpenAI, Anthropic, Vertex AI, and GitHub's AI ecosystem. * Oversee enterprise-grade deployment pipelines using OpenShift (OCP), Kubernetes, and robust CI/CD patterns to ensure reliable production delivery. * Establish engineering best practices across Python, TypeScript, and React for modern, AI-enabled applications. * Guide prompt engineering, skill engineering, and model evaluation approaches including guardrails, observability, red teaming, and hallucination detection. * Lead and mentor engineering pods , providing technical direction, career development, and architectural guidance. * Ensure systems are fully observable, monitored, and resilient, integrating fallback logic and safety controls to mitigate model and system failures. * Partner closely with UI/UX, platform, cybersecurity, and governance teams to deliver compliant, user-centric, and secure AI solutions at enterprise scale. * Collaborate with business stakeholders and product owners to align AI capabilities with strategic outcomes and define delivery roadmaps. * Ensure compliance with cybersecurity, data privacy, and model risk management standards required in regulated financial-services environments. * Resolve complex technical issues, escalating and troubleshooting challenges across AI pipelines, backend services, front-end apps, and infrastructure. * Lead Agile delivery processes, driving sprint execution, backlog prioritization, risk mitigation, and cross-team coordination. * Be well versed in emerging AI technologies, staying current with LLM advancements, evaluation techniques, vector search, and responsible AI practices. * Collaborate and influence across all levels, including senior managers, platform teams, and cross-functional partners to advance the AI engineering strategy., Technical Leadership * Lead end-to-end design and implementation of AI systems including chatbots, Retrieval-Augmented Generation (RAG), autonomous agents, and workflow automation tools. * Architect scalable, secure solutions leveraging industry-leading AI providers (OpenAI, Anthropic, Google Vertex AI, GitHub Copilot). * Oversee production deployment pipelines using OCP (OpenShift Container Platform) for containerization, orchestration, and runtime operations. * Define best practices for Python, TypeScript, and React development within AI-enabled applications. Project Delivery & Team Management * Manage and mentor pod teams (approx. 4 / 6 engineers each), ensuring high-quality execution and technical rigor. * Drive delivery roadmaps, project sequencing, and risk mitigation across multiple concurrent AI initiatives. * Partner with UI/UX designers to build intuitive, compliant, and enterprise-ready user experiences. * Guide prompt engineering, skill engineering, and evaluation frameworks for AI model tuning and safety. Operational Excellence * Ensure all AI deployments meet enterprise security, data privacy, and regulatory compliance standards required in Corporate & Investment Banking. * Collaborate with cybersecurity, risk, and governance teams to enforce secure coding, model-handling, and data-access patterns. * Design robust observability, monitoring, and fallback strategies for AI-driven production systems. Collaboration & Stakeholder Engagement * Work closely with product owners, business stakeholders, and platform teams to align AI capabilities with business outcomes. * Communicate feasibility, architectural trade-offs, delivery timelines, and technical risks. * Stay current with industry trends, emerging AI technologies, model evaluation techniques, and AI governance standards. ## Related Videos - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Reducing LLM Calls with Vector Search Patterns - Raphael De Lio (Redis)](https://www.wearedevelopers.com/videos/1714-reducing-llm-calls-with-vector-search-patterns-raphael-de-lio-redis) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [The AI-Ready Stack: Rethinking the Engineering Org of the Future](https://www.wearedevelopers.com/videos/1706-the-ai-ready-stack-rethinking-the-engineering-org-of-the-future) - [Accelerating Authentication Architecture: Taking Passwordless to the Next Level](https://www.wearedevelopers.com/videos/733-accelerating-authentication-architecture-taking-passwordless-to-the-next-level) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)