Senior AI Engineer

EchoStar • Herndon, VA

20h

About The Position

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.

Requirements

• 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
• 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

Nice To Haves

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

Responsibilities

• 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

Benefits

• Flexible spending accounts
• HSA
• 401(k) Plan with company match
• ESPP
• Career opportunities
• Flexible time away plan

What This Job Offers

• Job Type: Full-time
• Career Level: Senior