Senior Agentic AI Engineer
About The Position
EchoStar is seeking a skilled and innovative Senior Agentic AI Engineer to design, build, and bring enterprise-grade AI solutions and autonomous multi-agent systems into production. The role focuses on developing scalable generative AI products that progress beyond experimental proof-of-concepts to deliver measurable business impact. The engineer will work with cross-functional teams to translate business requirements into technical agent specifications and scalable microservices, while applying Site Reliability Engineering principles to ensure system reliability and observability. Candidates must be willing to participate in at least one in-person interview. Visa sponsorship is not available for this role. Compensation ranges from $134,406 to $181,844 per year, with individual total compensation varying based on qualifications, skills, competencies, and location.
Requirements
- Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or a related technical field.
- At least 4 years of experience in software development or data science.
- At least 4 years of experience with Python.
- At least 4 years of experience with microservices architecture.
- Advanced Python coding skills and a deep understanding of backend frameworks and distributed microservices architecture.
- Deep understanding of agent interoperability and communication standards, including MCP and A2A protocol design.
- AI engineering proficiency with cloud-based foundation model platforms, specifically AWS Bedrock or enterprise equivalents.
- Technical expertise in containerization, CI/CD pipelines, and cloud infrastructure.
- Proven track record of shipping LLM-powered systems into live production environments.
- Willingness to participate in at least one in-person interview.
Nice To Haves
- Experience with multi-agent orchestration frameworks such as LangGraph, CrewAI, or AutoGen.
- Familiarity with agent deployment platforms and infrastructure hosting, such as Bedrock AgentCore or equivalent production-grade hosting environments.
- Experience with big data platforms and distributed systems for large-scale context processing.
Responsibilities
- Design, develop, and deploy autonomous AI services and multi-agent workflows from concept through enterprise production.
- Implement MCP integrations for agent-to-tool communication and A2A integrations for secure agent-to-agent coordination and task delegation.
- Architect hybrid control flows, state machines, and graphs for multi-step reasoning, balancing probabilistic LLM behavior with deterministic code paths for critical backend transactions.
- Integrate secure tool execution environments using sandboxed contexts and strict egress controls.
- Collaborate with cross-functional teams to translate business requirements into technical agent specifications and scalable microservices.
- Apply SRE principles to agent behavior, including fallback mechanisms, circuit breakers, audit trails, observability, and reliability.
Benefits
- Flexible spending accounts
- Health savings account (HSA)
- 401(k) plan with company match
- Employee stock purchase plan
- Career opportunities
- Flexible time away plan
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What This Job Offers
Job Type
Full-time
Career Level
Senior
