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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Forward Deployed Engineer- AWS - **Company:** Deloitte T.T.L. - **Location:** San Antonio, TX, United States - **Experience:** Expert - **Salary:** $155,600.0 - $306,800.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Code Review, Continuous Integration, Information Engineering, Monitoring of Systems, Identity and Access Management, Software Engineering, Data Streaming, Management of Software Versions, Data Logging, Google Cloud, Cloud Platform System, Feature Engineering, Large Language Models, Apache Spark, Model Validation, HybridCloud, Event Driven Architecture, AI Platforms, Information Technology, Low Latency, Data Management, Microservices - **Published:** July 16, 2026 - **Apply:** https://dejobs.org/x/x/2746F0740D7F4FC580D0F5612CFF53E0/job/ ## About the Role Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering. 5+ yearsof experience in software engineering, data engineering, data science, or analytics engineering. 1+ yearsof hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments 1+ years of experience with AWS AI&Data including hands on experience with one of the following key platforms/products;Amazon Bedrock, Bedrock Agents, Knowledge Bases, Guardrails 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions 1+ years of experience building reliable, maintainable, and well-documented code Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve Limited immigration sponsorship may be available Preferred qualifications Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking) Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation Experience withMLOps/LLMOpspractices: evaluation frameworks, model monitoring, and prompt management Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures Experienceoperatingwithin hybrid onshore/offshore teams Familiarity with security, privacy, and compliance considerations ## Description As a Senior FDE, you will work side by side withseniorfunctional and technicalclientteam membersto rapidly prototype and deliver high-impact GenAI-enabledsolutions.This requiresahighly motivatedpractitioner who moves with speed and precision,building working software, engaging confidently with senior stakeholders and engineers to bringmeasurablebusinessimpactfrom day one. Additional responsibilities include: Client Engagement Embed with clients to identify business needs and translate high-value GenAI use cases into solutions. Partner with leaders, product owners, architects, and engineers to align priorities and delivery. Lead working sessions to shape solutions and drive client outcomes. Prototype and deliver working AI solutions using industry expertise and emerging capabilities. Contribute independently within an FDE pod while mentoring newer team members. Coach client teams and end users on platform capabilities and AI enablement, while building trusted relationships, managing expectations, and supporting long-term engagement success. Drive end-to-end sales and delivery support by developing demos/POCs, contributing to proposals and orals, articulating business value, and documenting solutions for smooth client handoff and knowledge transfer. Strengthen team and organizational impact by mentoring other FDEs through design/code reviews and feedback, while contributing reusable components to intellectual capital. Solution Engineering Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms. Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls. Apply architecture decisions that balance quality, safety, latency, cost, and model risk. Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation. Design extensible functionality, support sprint sizing, and align solutions with senior team members. Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations. The team AI & Engineeringleverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements. ## Related Videos - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Swapping Low Latency Data Storage Under High Load](https://www.wearedevelopers.com/videos/746-swapping-low-latency-data-storage-under-high-load) - [How E.On productionizes its AI model & Implementation of Secure Generative AI.](https://www.wearedevelopers.com/videos/623-how-e-on-productionizes-its-ai-model-implementation-of-secure-generative-ai) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Unleash the power of 5G in your code: transform your apps](https://www.wearedevelopers.com/videos/1567-unleash-the-power-of-5g-in-your-code-transform-your-apps) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Got AI ideas but no money? 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