> Markdown version of [/jobs/ext/2007368-sr-gen-ai-developer](https://www.wearedevelopers.com/jobs/ext/2007368-sr-gen-ai-developer). 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). --- # SR Gen AI developer - **Company:** Cognizant Technology Solutions Corporation - **Location:** Concord, NH, United States (Remote available) - **Experience:** Expert - **Salary:** $120,000.0 - $135,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Microsoft Azure, Open Source Technology, Cloud Services, Azure Machine Learning, Data Logging, GitHub Copilot, Office365, Large Language Models, ONNX (Open Neural Network Exchange) Format, TensorRT - **Published:** August 9, 2026 - **Apply:** https://www.juju.com/job/00000000gm7ffj ## About the Role Our strength is built on our ability to work together. Our diverse backgrounds offer different perspectives and new ways of thinking. It encourages lively discussions, creativity, productivity, and helps us build better solutions for our clients. We want someone who thrives in this setting and is inspired to craft meaningful solutions through true collaboration. If you are content with ambiguity, excited by change, and excel through autonomy, we'd love to hear from you! ## Description We are seeking an **AI Developer** to design, build, and productionize end-to-end AI solutions across LLMs, RAG pipelines, model fine-tuning, and cloud deployments. This role will work closely with product, engineering, and data teams to build scalable AI features that are reliable, performant, and secure in production environments. Responsibilities + Design and implement end-to-end AI features, including RAG systems, agent workflows, embeddings pipelines, and fine-tuned LLM applications. + Build and maintain data ingestion, chunking, embedding, retrieval, and prompt orchestration pipelines. + Fine-tune and evaluate open-source and proprietary LLMs using techniques such as LoRA, QLoRA, PEFT, and supervised fine-tuning. + Deploy and serve custom LLMs in Azure environments using Azure Machine Learning, AKS, Container Apps, or related services. + Optimize inference performance using quantization, batching, model parallelism, and GPU-aware serving strategies. + Work with model formats such as Safetensors, GGUF, ONNX, and TensorRT for efficient loading, portability, and deployment. + Build scalable APIs and services for LLM inference, streaming responses, and model orchestration. + Implement model monitoring, logging, evaluation, prompt testing, and feedback loops. + Collaborate with product managers and stakeholders to translate business requirements into AI capabilities. + Explain technical trade-offs clearly to non-technical audiences, including model size, quantization, latency, cost, and accuracy. AI Skills All contractor resources are expected to demonstrate baseline proficiency in enterprise-approved AI tools as part of their day-to-day responsibilities. This includes, but is not limited to: + **Consistent Use:** Maintain a minimum of 90% weekly usage of AI tools such as GitHub Copilot, Microsoft 365 Copilot, and other GenAI platforms approved by the enterprise. + **Applied Productivity:** Leverage AI tools to enhance coding, documentation, data analysis, and decision-making workflows. + **Continuous Learning:** Stay current with evolving AI capabilities and features, and apply them to improve delivery quality and velocity. ## Related Videos - [Collaborative Intelligence: The Human & AI Partnership](https://www.wearedevelopers.com/videos/1097-collaborative-intelligence-the-human-ai-partnership) - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [Crypto-secure Data Management with In-Database Blockchain](https://www.wearedevelopers.com/videos/632-crypto-secure-data-management-with-in-database-blockchain) - [Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure](https://www.wearedevelopers.com/videos/1532-agentic-ai-from-theory-to-practice-developing-multi-agent-ai-systems-on-azure) - [Efficient deployment and inference of GPU-accelerated LLMs​](https://www.wearedevelopers.com/videos/929-efficient-deployment-and-inference-of-gpu-accelerated-llms) - [Build Delightful Mobile Experiences with Kotlin, Realm, and Atlas Device Sync](https://www.wearedevelopers.com/videos/694-build-delightful-mobile-experiences-with-kotlin-realm-and-atlas-device-sync) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Got AI ideas but no money? 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