> Markdown version of [/jobs/ext/1898308-gen-ai-engineer](https://www.wearedevelopers.com/jobs/ext/1898308-gen-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Gen AI Engineer - **Company:** Infosys - **Location:** Charlotte, NC, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Microsoft Azure, Code Review, Databases, Continuous Integration, Cursor (Graphical User Interface Elements), DevOps, Github, Python (Programming Language), Knowledge Management, Open Source Technology, SAS (Software), Systems Integration, TypeScript, Scripting, GitHub Copilot, ReactJS, Large Language Models, Multi-Agent Systems, Prompt Engineering, Deep Learning, Git, Fastapi, Kubernetes, Machine Learning Operations, Front End Software Development, Terraform, Docker, Microservices - **Published:** August 1, 2026 - **Apply:** https://sjobs.brassring.com/TGnewUI/Search/home/HomeWithPreLoad?partnerid=25633&siteid=5439&PageType=JobDetails&jobid=2247935 ## About the Role * Python and hands-on building of enterprise GenAI applications with Lang Chain, Lang Graph, Llama Index, or similar orchestration frameworks; comfortable with RAG, vector databases, agentic workflows (tool calling, memory, multi-agent), and prompt engineering. * Working with Azure OpenAI, AWS Bedrock, OpenAI, Anthropic, or similar LLM platforms; integrating with enterprise APIs, databases, and knowledge repositories. * Building production APIs and microservices with Fast API, Docker, and Kubernetes; software engineering fundamentals (system design, testing, CI/CD, Git); hands-on with AI coding assistants (GitHub Copilot, Claude Code, Cursor) for engineering productivity. * LLMOps practices - observability, tracing, evaluation (RAGAS, DeepEval, Lang Smith), guardrails, cost governance, and model safety. * conducting code reviews, driving technical decisions, and collaborating with product and platform teams., * Open-source LLMs (Llama, Mistral, Gemma) and fine-tuning techniques (LoRA, QLoRA, PEFT); familiarity with Model Context Protocol (MCP). * Multimodal AI (vision-language, OCR, speech) and document intelligence. * Front-end (React, TypeScript), DevOps/IaC tooling (GitHub Actions, Terraform, Helm), and domain exposure across financial services, telecom, retail, or healthcare, * Bachelor's degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education. * This position may require relocation and/or travel to work/project location. * All applicants authorized to work in the United States are encouraged to apply. ## Description In the assigned Job Role of Data Science Consultant 2, your Area Of Responsibility will be as below: * Develop data preparation tasks, while identifying patterns or anomalies. * Ensure data readiness for advanced modeling. * Develop models for complex use cases (e.g., forecasting models, LLM-based solutions), while refining algorithms to meet business needs, and ensure smooth deployment into scalable, production-ready solutions. * Conduct testing and optimize algorithms for performance, reliability, and scalability, while providing guidance to team members in best practices. * Design and develop predictive models and data-driven analyses to address business challenges. * Build, evaluate, and deploy models, standardize code, and contribute to knowledge management. * Leverage tools like SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions. * Define analytics problems for projects; execute visualization, analysis, and predictive modeling under guidance. * Proactively maintain models and implement improvements for accuracy and reliability. * Apply governance controls to mitigate risks and ensure compliance. * Analyze performance trends, recommend improvements, and document discrepancies for escalation. * Maintain comprehensive documentation standards, while participating in knowledge transfer sessions. * Participate in discussions with stakeholders to refine requirements, provide insights, and guide implementation of models. * Apply the predefined quality measurement framework at an individual task level in the project. * Deploy complex analytics tools or multi-system integration, while validating deployment success. * Participate in developing scripts or templates for repeated deployments tasks. * Contribute to analytic solutions, IP asset creation, and training initiatives. * Contribute to thought leadership such as papers, innovative non-ML, ML, deep learning or LLM models, and proofs of concepts. * Participate in and deliver analytics training, while contributing to content creation. * Provide input for segment and unit-level business plans. Your contribution to the team: * Deliver scalable, high-quality analytics solutions aligned to business needs. * A knack for optimization, deployment and performance improvement of models. * The ability to drive innovation through advanced analytics, automation and thought leadership. * Enable team growth through knowledge sharing, training and standardization. * Support business planning with data-driven insights. ## Related Videos - [AI Killed DevOps... 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Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud)