Dish Tv
From Dish Tv's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
Compensation is based on the role's location and is subject to change.
Enterprise operations require AI-driven solutions to optimize network performance, elevate customer experience, and streamline workflows. This senior role owns the delivery of 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.
Candidates must be willing to participate in at least one in-person interview, which may include a live whiteboarding or technical assessment session.
Own the design, build, and deployment of autonomous AI agents and securely grounded RAG pipelines using Amazon Bedrock, OpenSearch, and Model Context Protocol (MCP) to execute complex business tasks
Make architecture and security decisions for Guardrails for Amazon Bedrock and cloud security protocols; ensure responsible AI usage, data privacy, and prompt injection protection across enterprise applications
Lead the design and maintenance of low-latency RESTful APIs and MLOps pipelines on AWS infrastructure to support continuous model training, evaluation, fine-tuning, and real-time inference
Drive alignment of AI engineering deliverables with departmental OKRs and operational goals by working with enterprise engineers, data scientists, and business stakeholders
Optimize network performance and customer experience by independently integrating scalable deep learning, NLP, and LLM microservices into existing backend enterprise systems
Core Skills, Competencies, and Key Experiences (What you’ll bring)
Experience building and deploying end-to-end Generative AI applications, RAG frameworks, and agentic workflows in production cloud environments, and can show how you resolved complex technical challenges along the way
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
Independent judgment 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: Bachelor's Degree in Computer Science, Data Science, AI/ML, or an applicable technical degree
Minimum Experience: 4+ years of experience in AI/ML engineering, cloud software development, or a related role
Required Technical Skills: Must have at least 4+ 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
#LI-JZ2
Salary Range
About Our Department
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 role's 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 echostar.com and jobs.echostar.com accessible to users. Please contact leaves@dish.com 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 Recruiting@Dish.com.
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.
Own the design, build, and deployment of autonomous AI agents and securely grounded RAG pipelines using Amazon Bedrock, OpenSearch, and Model Context Protocol (MCP) to execute complex business tasks
Make architecture and security decisions for Guardrails for Amazon Bedrock and cloud security protocols; ensure responsible AI usage, data privacy, and prompt injection protection across enterprise applications
Lead the design and maintenance of low-latency RESTful APIs and MLOps pipelines on AWS infrastructure to support continuous model training, evaluation, fine-tuning, and real-time inference
Drive alignment of AI engineering deliverables with departmental OKRs and operational goals by working with enterprise engineers, data scientists, and business stakeholders
Optimize network performance and customer experience by independently integrating scalable deep learning, NLP, and LLM microservices into existing backend enterprise systems
Experience building and deploying end-to-end Generative AI applications, RAG frameworks, and agentic workflows in production cloud environments, and can show how you resolved complex technical challenges along the way
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
Independent judgment 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: Bachelor's Degree in Computer Science, Data Science, AI/ML, or an applicable technical degree
Minimum Experience: 4+ years of experience in AI/ML engineering, cloud software development, or a related role
Required Technical Skills: Must have at least 4+ 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
#LI-JZ2
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