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Aws Engineer Jobs in Georgetown, TX (NOW HIRING)

If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations. Work you'll do As an AWS AI&Data FDE, you ...

AWS Architect

Georgetown, TX · Hybrid

$60.25 - $79/hr

Ability to design/recommend backup and DR solutions for AWS instances Support and guide AWS developers and Devops engineers Good communication skills Additional Information All your information will ...

AWS Databricks Developer

Austin, TX · On-site

$55 - $60/hr

As a AWS Databricks Developer you will be a part of an Agile team to build healthcare applications and implement new features while adhering to the best coding development standards

AWS Architect

Austin, TX · On-site

$140 - $200/hr

AWS Architect Location: Austin, TX (onsite) Applicants must be authorized to work for any employer ... Collaborate with development, DevOps, and QA teams to establish best practices and technical ...

AWS Architect

Austin, TX · On-site

$64.50 - $84.75/hr

Collaborate with development, DevOps, and QA teams to establish best practices and technical ... Knowledge of AWS services such as EC2, Lambda, S3, API Gateway, RDS, IAM, VPC, and CloudWatch.

AWS Software Developer

Austin, TX · Remote

$90K - $115K/yr

TTEC Digital seeks an AWS Software Developer to join our AWS Partner Practice. This is a remote role based in the United States. The TTEC Digital AWS Partner Practice, comprised of over 150 brilliant ...

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Aws Engineer information

See Georgetown, TX salary details

$36.2K

$94.5K

$127.8K

How much do aws engineer jobs pay per year?

As of Aug 10, 2026, the average yearly pay for aws engineer in Georgetown, TX is $94,540.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,000.00 and $108,200.00 per year, depending on experience, location, and employer.

Are AWS engineer jobs still in demand?

AWS engineer jobs remain in high demand due to the widespread adoption of cloud computing and the need for expertise in AWS services, cloud architecture, and security. Organizations continue to seek professionals with certifications like AWS Certified Solutions Architect to manage and optimize their cloud infrastructure.

What does an AWS engineer do?

An AWS engineer designs, implements, and manages cloud infrastructure using Amazon Web Services. They configure services such as EC2, S3, and RDS, ensure security and scalability, and often hold certifications like AWS Certified Solutions Architect. Their work involves scripting, monitoring, and optimizing cloud environments to support business needs.

What are the key skills and qualifications needed to thrive as an AWS engineer?

To thrive as an AWS Engineer, you need expertise in cloud computing, networking, and security, typically backed by a degree in computer science or a related field and relevant AWS certifications. Familiarity with AWS services (such as EC2, S3, Lambda), Infrastructure as Code tools (like CloudFormation or Terraform), and CI/CD pipelines is essential. Strong problem-solving skills, attention to detail, and effective communication set top performers apart in this role. These skills and qualities are crucial for designing secure, scalable, and efficient cloud solutions that meet business objectives.

What is an AWS engineer?

AWS Engineers are IT professionals who design, implement, and manage cloud-based solutions using Amazon Web Services (AWS). They work on deploying, maintaining, and optimizing cloud infrastructure and services to meet organizational needs. Their responsibilities often include configuring servers, setting up networking and security, automating deployments, and ensuring high availability and scalability. AWS Engineers typically need strong knowledge of AWS tools, cloud architecture, and DevOps practices. They may also help organizations migrate applications and data to the AWS cloud.

What are some common challenges AWS engineers face when managing cloud infrastructure, and how can they address them?

AWS Engineers often encounter challenges such as optimizing costs, ensuring security compliance, and managing scalability as cloud environments grow. Staying updated with AWS best practices and using automation tools like AWS CloudFormation or Terraform can help address these issues. Regularly monitoring usage, implementing proper access controls, and keeping up with AWS service updates are essential strategies to maintain efficient and secure infrastructure.

What is the difference between Aws Engineer vs Cloud Solutions Architect?

AspectAws EngineerCloud Solutions Architect
CertificationsAWS Certified Solutions Architect – Associate, AWS Certified DeveloperAWS Certified Solutions Architect – Associate, AWS Certified Cloud Practitioner
Primary RoleImplementing, managing, and maintaining AWS cloud infrastructureDesigning and planning cloud solutions to meet business needs
Work EnvironmentHands-on technical tasks, deployment, and troubleshootingDesign and architecture planning, client interaction
Industry UsageIT, cloud service providers, enterprise companies

While Aws Engineers focus on deploying and managing cloud infrastructure, Cloud Solutions Architects primarily design cloud solutions and strategies. Both roles require AWS certifications and are integral to cloud projects, but their daily tasks and responsibilities differ significantly.

What is the salary of AWS engineer?

The average salary of an AWS engineer varies based on experience, location, and certifications but typically ranges from $80,000 to $150,000 annually. Senior roles with advanced skills in cloud architecture and DevOps can earn higher salaries, especially in high-demand markets.
What are popular job titles related to Aws Engineer jobs in Georgetown, TX? For Aws Engineer jobs in Georgetown, TX, the most frequently searched job titles are:
What job categories do people searching Aws Engineer jobs in Georgetown, TX look for? The top searched job categories for Aws Engineer jobs in Georgetown, TX are:
What cities near Georgetown, TX are hiring for Aws Engineer jobs? Cities near Georgetown, TX with the most Aws Engineer job openings:
Infographic showing various Aws Engineer job openings in Georgetown, TX as of August 2026, with employment types broken down into 90% Full Time, 6% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $94,540 per year, or $45.5 per hour.

Forward Deployed Engineer- AWS

Deloitte

Austin, TX • On-site

Full-time

Re-posted 2 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 150 rated financial services


Job description

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.


Work you'll do

As an AWS AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from 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.


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 & Engineering leverages 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.


Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 3+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of 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 AgentCore, Strands Agents SDK, Knowledge Bases, Guardrails
  • 1+ years of experience with AWS Neptune and OpenSearch
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • At least 3 of 6 certifications from the following list: AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate)
  • 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 with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience with SageMaker fine-tuning (SFT and RFT) for domain SLMs
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations


The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.


You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


Qualifications:

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.


Work you'll do

As an AWS AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from 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.


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 & Engineering leverages 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.


Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 3+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of 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 AgentCore, Strands Agents SDK, Knowledge Bases, Guardrails
  • 1+ years of experience with AWS Neptune and OpenSearch
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • At least 3 of 6 certifications from the following list: AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate)
  • 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 with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience with SageMaker fine-tuning (SFT and RFT) for domain SLMs
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations


The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.


You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


Education:Bachelor's DegreeEmployment Type:

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