AI Engineer II

Candidates must be willing to participate in at least one in-person interview which may include a live whiteboarding or technical assessment session.

Enterprise operations require AI-driven solutions to optimize network performance elevate customer experience and streamline workflows. This role addresses the need for scalable ML models real-time analytics frameworks and intelligent automation pipelines across enterprise and cloud-native environments. The position bridges strategy and deployment by transforming complex business requirements into robust secure AI microservices that deliver measurable performance outcomes.

• Build and deploy autonomous AI agents and securely grounded RAG pipelines using Amazon Bedrock OpenSearch and Model Context Protocol (MCP) to execute complex business tasks

• Implement Guardrails for Amazon Bedrock and cloud security protocols to ensure responsible AI usage data privacy and prompt injection protection across enterprise applications

• Design and maintain low-latency RESTful APIs and MLOps pipelines on AWS infrastructure to support continuous model training evaluation fine-tuning and real-time inference

• Partner with enterprise engineers data scientists and business stakeholders to align AI engineering deliverables with departmental OKRs and operational goals

• Optimize network performance and customer experience by integrating scalable deep learning NLP and LLM microservices into existing backend enterprise systems

• Critical experience in building and deploying end-to-end Generative AI applications RAG frameworks and agentic workflows in production cloud environments

• Advanced technical proficiency in Python asynchronous API development using FastAPI and data manipulation with Pandas and NumPy

• Demonstrated mastery of MLOps best practices including CI/CD automation containerization with Docker model monitoring and cloud orchestration on AWS

• Strong problem-solving abilities and AI application skills focused on integrating Model Context Protocol (MCP) standards and managing large data processing pipelines

• Collaborative leadership and clear decision-making skills to translate cross-functional business requirements into secure compliant technical solutions

• Familiarity with Amazon NLX and multi-agent frameworks such as LangGraph or AutoGen

• Minimum Education: Bachelors Degree in Computer Science Data Science AI/ML or an applicable technical degree
• Minimum Experience: 2 years of experience in AI/ML engineering cloud software development or a related role
• Required Technical Skills: Must have at least 2 years of experience with:

  • Python Pandas NumPy and API development using FastAPI

  • AWS AI stack including Amazon Bedrock (Knowledge Bases Guardrails Agents) and Amazon SageMaker

  • Docker containerization CI/CD pipelines and production MLOps workflows

Our Technology teams challenge the status quo and reimagine capabilities across industries. Whether through research and development technology innovation or solution engineering our team members play a vital role in connecting consumers with the products and platforms of tomorrow.

EchoStar is reimagining the future of connectivity. Our business reach spans satellite television service live-streaming and on-demand programming smart home installation services mobile plans and products.

Today our brands include Boost Mobile DISH TV Gen Mobile Hughes and Sling TV.

We offer meaningful health perks including flexible spending accounts HSA a 401(k) plan with company match employee stock purchase plan career opportunities and a flexible time away plan. Review a benefits summary here: EchoStar Benefits

The base pay range shown is a guideline. Individual total compensation will vary based on factors such as qualifications skill level and competencies. Compensation is based on the roles location and is subject to change.

Candidates need to successfully complete a pre-employment screen which may include a drug test and DMV check. Our company is committed to fostering an inclusive and equitable workplace where every individual has the opportunity to succeed. We are dedicated to providing individuals with criminal or arrest records a fair chance of employment in accordance with local state and federal laws.

This job posting will be active for a minimum of 3 days and will continue to extend by 3 days until the position is filled.

We pride ourselves on developing and promoting talent as an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin disability or protected veteran status. EchoStar will accommodate the sincerely held religious beliefs of employees if such accommodations are not undue hardships and are otherwise within the bounds of applicable law. All qualified applicants with arrest or conviction records will be considered for employment in accordance with local state and federal law. You may redact any information that identifies age date of birth or dates of school/graduation from your application documents before submission and throughout our application process.

EchoStar will provide reasonable accommodation to otherwise qualified job applicants and employees with known physical or mental disabilities unless doing so poses an undue hardship on the Company poses a direct threat of substantial harm to others or is otherwise not required by law. EchoStar has a more detailed Accommodation Policy that applies to employees. EchoStar endeavors to make and accessible to users. Please contact if you would like to discuss the accessibility of our website or need assistance completing the application process. This contact information is for accommodation requests only; do not use this contact information to inquire about the status of applications. If you have questions regarding your application or the recruitment process please email .

Click the links to access the following statements: EEO Policy Statement Pay Transparency EEOC Know Your Rights (English/Spanish)

Candidates must be willing to participate in at least one in-person interview which may include a live whiteboarding or technical assessment session.

Enterprise operations require AI-driven solutions to optimize network performance elevate customer experience and streamline workflows. This role addresses the need for scalable ML models real-time analytics frameworks and intelligent automation pipelines across enterprise and cloud-native environments. The position bridges strategy and deployment by transforming complex business requirements into robust secure AI microservices that deliver measurable performance outcomes.

• Build and deploy autonomous AI agents and securely grounded RAG pipelines using Amazon Bedrock OpenSearch and Model Context Protocol (MCP) to execute complex business tasks

• Implement Guardrails for Amazon Bedrock and cloud security protocols to ensure responsible AI usage data privacy and prompt injection protection across enterprise applications

• Design and maintain low-latency RESTful APIs and MLOps pipelines on AWS infrastructure to support continuous model training evaluation fine-tuning and real-time inference

• Partner with enterprise engineers data scientists and business stakeholders to align AI engineering deliverables with departmental OKRs and operational goals

• Optimize network performance and customer experience by integrating scalable deep learning NLP and LLM microservices into existing backend enterprise systems

• Critical experience in building and deploying end-to-end Generative AI applications RAG frameworks and agentic workflows in production cloud environments

• Advanced technical proficiency in Python asynchronous API development using FastAPI and data manipulation with Pandas and NumPy

• Demonstrated mastery of MLOps best practices including CI/CD automation containerization with Docker model monitoring and cloud orchestration on AWS

• Strong problem-solving abilities and AI application skills focused on integrating Model Context Protocol (MCP) standards and managing large data processing pipelines

• Collaborative leadership and clear decision-making skills to translate cross-functional business requirements into secure compliant technical solutions

• Familiarity with Amazon NLX and multi-agent frameworks such as LangGraph or AutoGen

• Minimum Education: Bachelors Degree in Computer Science Data Science AI/ML or an applicable technical degree
• Minimum Experience: 2 years of experience in AI/ML engineering cloud software development or a related role
• Required Technical Skills: Must have at least 2 years of experience with:

  • Python Pandas NumPy and API development using FastAPI

  • AWS AI stack including Amazon Bedrock (Knowledge Bases Guardrails Agents) and Amazon SageMaker

  • Docker containerization CI/CD pipelines and production MLOps workflows